Ombeline Méric
email: ombeline.meric@ujf-grenoble.fr

Stéphane Garambois

Jean-Philippe Malet

Héloise Cadet

Philippe Guéguen

Denis Jongmans

SEISMIC NOISE-BASED METHODS FOR SOFT-ROCK LANDSLIDE CHARACTERIZATION

Keywords: seismic noise, soft rock landslide, in-situ characterization, 3D geometry

In order to better understand the mechanics and dynamic of landslides, it is of primary interest to image correctly their internal structure. Several active geophysical methods are able to provide the geometry of a given landslide, but were rarely applied in 3 dimensions in the past.

The main disadvantages of methods like seismic reflection or electrical tomographies are that there are heavy to set up, require for some heavy processing tools to implement, and consequently are expensive and time consuming. Moreover, in the particular case of soft-rock landslides, their respective sensitivity and resolution are not always adequate to locate the potential slip surfaces. The passive methods, which require lighter instrumentation and easier processing tools, can represent an interesting alternative, particularly for difficult accessible landslides. Among them, the seismic noise based methods have shown increasing applications and developments, in particular for seismic hazard mapping in urban environment. In this paper, we present seismic noise investigations carried out on two different sites, a mudslide and a translational clayey landslide where independent measurements (geotechnical and geophysical tests) were performed earlier. Our investigations were composed of H/V measurements, which are fast and easy to perform in the field, in order to image shear wave contrasts (slip surfaces), and seismic noise array method, which is heavier to apply and interpret, but provides S-waves velocity profile versus depth. The comparisons between geophysical investigations and geotechnical information proved the applicability of such passive methods in 3D complexes, but also some limitations. Indeed interpretation of these measurements can be tricky in rough and non-homogeneous terrains.

CARACTERISATION DE GLISSEMENTS ARGILEUX PAR DES METHODES DE BRUIT DE FOND SISMIQUE

Mots clés : bruit de fond sismique, glissement argileux, caractérisation in-situ, géométrie 3D RESUME Afin d'identifier les mécanismes de contrôle et de caractériser la dynamique de glissements de terrain, il est impératif d'imager correctement leur structure interne. Plusieurs méthodes géophysiques actives sont utilisables pour identifier la géométrie d'un glissement de terrain, mais leurs potentialités ont été rarement testées dans des environnements fortement 3D. Les principaux inconvénients de méthodes géophysiques telles que la sismique réflexion ou la tomographie électrique sont la difficulté de mise en oeuvre et la complexité des traitements de données, ce qui les rend chères et consommatrices en temps. De plus, pour le cas particulier de glissements argileux, leur sensibilité et résolution ne sont pas toujours adaptées à la détection des surfaces de glissement. Les méthodes géophysiques passives, qui offrent l'avantage d'une instrumentation légère et d'un traitement des données plus simple, représentent ainsi une alternative intéressante, particulièrement pour des sites difficiles d'accès. Parmi celles-ci, les méthodes de bruit sismique ambiant connaissent depuis quelques années des développements et applications intéressants, notamment pour le zonage de l'aléa sismique en milieu urbain. Nous présentons dans ce papier des investigations par bruit de fond sismique effectuées sur deux sites instables, un glissement-coulée et un glissement translationnel, où des investigations géotechniques et géophysiques indépendantes ont été réalisées. Nos investigations se composent (1) de mesures H/V, simples, légères et rapides à

INTRODUCTION

The authorities with the responsibility of protecting livelihood and infrastructure from the threat of landslide hazard must be particularly concerned with three critical aspects: (1) the spatial distribution of the processes, (2) the understanding of their mechanisms, (3) their magnitude and temporal frequency. These purposes imply to accurately assess the characteristics of the landslides and to evaluate their controlling factors (climate, seismology) in a dynamic dimension. For these reasons, 2D and 3D mathematical models have been developed during the last decade in order to simulate the complexity of landslide mechanisms [START_REF] Commend | -3D numerical modelling of a landslide in Switzerland[END_REF][START_REF] Van Asch T | Forecasting the behaviour of complex landslides with a spatially distributed hydrological model[END_REF][START_REF] Tacher | Modelling the behaviour of large landslide with respect to hydrogeological and geomechanical parameter heterogeneity -Landslides[END_REF]. At this time, one of their main weaknesses lies in the large uncertainty of parameters describing the unstable area. For example, critical information, such as the 3D geometry of a landslide and of its surrounding geology, its geomechanical and hydrological properties, or its internal discontinuities, as well as the uncertainties associated to these parameters are rarely available.

Landslides are generally studied using geotechnical investigations (boreholes, penetrometric tests, etc), local instrumentation placed in boreholes (piezometers, inclinometers), as well as detailed geomorphological observations [START_REF] Antoine | Geotechnical problems caused by glaciolacustrine clays in the French Alps[END_REF][START_REF] Malet J.-P | Integrated investigations on landslides: example of the Super-Sauze earthflow[END_REF]. Even if these studies are essential because they provide direct information of the landslide material, their cost and limited spatial representativeness hinder their use for 3D studies. In particular, except by multiplying the number of tests, these methods are not able to image the lateral variability of landslide characteristics. To address this problem, a large choice of geophysical methods is available on a broad spatial scale. An increasing trend to apply geophysical studies for landslides characterization has been recently observed, mainly thanks to the improvement of data acquisition systems and of data inversion softwares. A critical review of these methods is discussed by [START_REF] Jongmans | Surface geophysical and monitoring of landslides: a review -Bull[END_REF] this issue], who point out the need of combining geophysical methods [see also Israil and Pachani, 2003] and of validating geophysical data by geotechnical information [START_REF] Maquaire | Une approche multidisciplinaire pour la connaissance d'un glissement coulée dans les marnes noires du Callovien-Oxfordien (Super-Sauze, Alpes de Haute Provence[END_REF][START_REF] Malet J.-P | Integrated investigations on landslides: example of the Super-Sauze earthflow[END_REF]. In practise, the high cost, time consuming efforts and difficulties in implementing 3D geophysical investigations can only be considered for active landslides presenting a high level of risk or for research purposes. Consequently, fast methods, easy to deploy and presenting lower costs have to be developed in the future, at least to locate the slip surfaces and characterize bedrock geometries in 3D. Methods based on seismic noise measurements, which were extensively applied for seismic hazard mapping in the recent years, fill close criteria [START_REF] Asten | Passive seismic methods using the microtremor wave field for engineering and earthquake site zonationEds[END_REF].

In this paper, we present two examples of seismic noise investigations performed on two soft-rock landslides of the South French Alps (fig. 1), ie. the Super-Sauze mudslide in the black marls of the Ubaye valley and the Saint-Guillaume translational landslide in the varved clays of the Trièves region. At both sites, the slip surfaces are located within a homogeneous clay formation. The purposes of our studies are to evaluate the potential of seismological data, first to detect the slip surfaces using the H/V spectral ratio and second, to derive S-wave velocity profiles using seismic noise networks. To our knowledge, only a few seismic noise investigations were performed in the past on landslides. Galippolli et al. [2000] briefly mentioned the use of H/V methods on the large Giarossa landslide (southern Italy) which helped to interpret electrical tomography images. Recently, Méric et al [2005] failed to identify the slip surface of the large rocky landslide of Séchilienne using H/V measurements.

They however noted a clear correlation between amplitude of the seismic noise and the landslide displacement rate explained by fracture density.

As both Super-Sauze and Saint-Guillaume landslides were characterized and monitored using geotechnical and geophysical measurements, a critical discussion of results provided by seismic noise methods is thus possible.

SEISMIC NOISE THEORY

The H/V method consists in computing the spectral ratio between horizontal and vertical components of the seismic noise recorded simultaneously at a given location with a 3D seismometer placed at the ground surface. Nogoshi & Igarashi [1972] first proposed the use of the H/V method as a tool for the estimate of the seismic response of the surface layers. This method has since been widely diffused around the world by [START_REF] Nakamura | A method for dynamic characteristics estimation of subsurface using microtremor on groung surface -QR of[END_REF]. Since 1989, because of its low-cost and its fast deployment, the use of the H/V method has become widespread, mainly with the objective of detecting the sedimentary zones that could amplify seismic ground motion. The validation of the H/V spectral ratio using noise has been since confirmed both experimentally [START_REF] Lermo | Site effect evaluation using spectral ratios with only one station[END_REF][START_REF] Field | A comparison and test of various site-response estimation techniques including three are not reference-site dependent[END_REF][START_REF] Guéguen | An indication of the soil topmost layer response in Quito (Ecuador) using H/V spectral ratio[END_REF][START_REF] Lebrun | A site effect study in urban area: experimental results in Grenoble (France) -Pageoph[END_REF]] and from theoretical and numerical studies [START_REF] Field | The theoretical response of sedimentary layers to ambient seismic noise[END_REF][START_REF] Lachet | Numerical and theorical investigations on the possibilities and limitations of the "Nakamura's" technique. -Journal of Physics of the Earth[END_REF][START_REF] Cornou | Simulation of seismic ambient vibrations -II: H/V and array techniques for real sites[END_REF][START_REF] Bonnefoy-Claudet S | Nature du bruit de fond sismique : implications pour les études des effets de site[END_REF]]. In the case of a stratified soil profile composed of a soft layer at the top of a stiffer layer, the 1D amplified frequency f 0 may be estimated according to the equation f 0 =Vs/4Hs, where Hs is the thickness and Vs the shear wave velocity of the topmost layer, respectively and when the Swave contrast is sufficiently large [START_REF] Bonnefoy-Claudet S | Nature du bruit de fond sismique : implications pour les études des effets de site[END_REF]. As outlined by the equation linking f 0 to Hs, knowing the shear wave velocity Vs of the upper layer is fundamental to deduce the thickness of this layer. This information can be derived from S-wave refraction or surface wave analyses. Nevertheless, the simple relation linking fundamental frequency, shear wave velocity and depth is valid according to a 1D model assumption that is not the geometry of most valleys. For example, while [START_REF] Bard | The two-dimensional resonance of sediment-filled valleys -Bull[END_REF] discussed the 2D model shapes of a theoretical valley, [START_REF] Steimen | Identifying 2-D Resonance in Microtremor Wave Fields -Bull[END_REF] and [START_REF] Roten | -2D resonances in Alpine valleys identified from ambient vibration wavefield[END_REF] recently showed experimentally the strong 2D effect of valley shape on the resonance frequency deduced from ambient seismic noise.

The shear wave velocity profile can also be obtained from seismic noise measurements recorded by an array of seismometers. This configuration allows to define the dispersion curve of the Rayleigh-wave phase velocity [for example, [START_REF] Tokimatsu | Geotechnical site characterization using surface waves[END_REF][START_REF] Satoh | Estimation of S-Wave Velocity Structures in and around the Sendai Basin, Japan, Using Array Records of Microtremors[END_REF][START_REF] Scherbaum | Determination of shallow shear wave velocity profiles in the Cologne/Germany area using ambient vibrations[END_REF]].

In the following, all dispersion curves deduced from active surface wave or from seismic noise network analyses, were computed using the conventional semblance-based frequencywavenumber method [Lacoss et al., 1969;[START_REF] Kvaerna | Stability of various f-k estimation techniques[END_REF]Ohrnberger, 2001], which provides a semblance map of the velocity (or slowness) and frequency of the waves travelling with the highest energy. The maximum of each semblance map has been picked.

The obtained dispersions curves were then inverted to obtain the S-wave vertical velocity profile (and eventually VP). For this, we used a neighbourhood algorithm inversion method where the computation time has been optimized [START_REF] Wathelet | Surface wave inversion using a direct search algorithm and its application to ambient vibration measurements[END_REF]. The method is a stochastic direct search method for finding models of acceptable data fit within a multidimensional parameter space [Sambridge, 1999a[Sambridge, & 1999b]]. Four parameters were investigated, ie. thickness, density, P-wave velocities and (above all) S-wave velocities of each layer. Thousands of direct models were tested and only those exhibiting lower RMS errors were kept. It should be noted that to reduce the number of models, the H/V resonance frequency of the central station was added as a priori information during the inversion process.

INVESTIGATION OF THE SUPER-SAUZE MUDSLIDE

Geological, geomorphological and geotechnical setting of the mudslide

The Super-Sauze mudslide (Ubaye valley) is one of the persistently active landslide (since the 1970's) occurring in black marls [START_REF] Maquaire | Black marl earthflows mobility and long-term seasonal dynamic in southeastern France[END_REF]. Its geological environment is very complex and is the consequence of the geological history of this alpine zone characterized by an overthrust of allochtonous sandstone and limestone formations over the autochtonous black marl bedrock. From the highest to the lowest elevations, the geological levels comprise: (1) the calcareous Klippe of Lan which overhangs the mudslide, (2) the moraine deposited by the Ubaye glacier during the Quaternary age, (3) the autochtonous bedrock consisting of Callovo-Oxfordian black marls with a grey clayey schist facies, very finely laminated and highly tectonized.

It is a clayey flow-like landslide characterized by a complex vertical structure associating a slip surface and a viscoplastic plug. Multidisciplinary observations (geology, geomorphology, geotechnics, hydrology) carried out since 1991 [Weber and Hermann, 2000;[START_REF] Malet J.-P | Integrated investigations on landslides: example of the Super-Sauze earthflow[END_REF] provide numerous information about its geology and geometry. The mudslide material consists of a silty-sand matrix mixed with moraine debris. It extents over an horizontal distance of 850 m and occurs between an elevation of 2105 m at the crown and 1740 m at the toe with an average 25° slope. Its total volume is estimated at 750,000 m 3 and velocities range from 0.01 to 0.4 m.day -1 [Malet and [START_REF] Maquaire | Black marl earthflows mobility and long-term seasonal dynamic in southeastern France[END_REF]. A detailed morphological description of the mudslide since its genesis can be found in Weber and Herrmann [2000]. The bedrock topography corresponds in the upper part to a succession of more or less parallel crests and gullies and in the medium and lower parts to a narrow and deeply incised channel.

Consequently its thickness is highly variable and varies between 0 and about 20 m. This geometrical scheme plays an essential role in the dynamics of the landslide by delimiting preferential water and material pathways and creating sections with differing kinematical, mechanical and hydrological characteristics. Its geotechnical structure consists in two superimposed units [START_REF] Malet J.-P | Integrated investigations on landslides: example of the Super-Sauze earthflow[END_REF][START_REF] Maquaire | Black marl earthflows mobility and long-term seasonal dynamic in southeastern France[END_REF]. The topmost unit, 5 to 9 m thick, is a very wet muddy formation, whereas the lowermost unit, with a maximum thickness of 10 m, is a stiff compact, relatively impervious and apparently stable formation.

The hillslopes delimitating the lateral extension of the mudslide are characterized by moraine deposits, 3 to 15m thick, especially on the eastern flank.

Electrical Tomographies

Six electrical tomographies were carried out on the mudslide allowing a pseudo-3D view of its internal structure (fig. 2, white lines). The tomographies were acquired using a Wenner configuration chosen for its high signal to noise ratio property and its sensitivity to horizontal contrasts, although the configuration is not adapted to precisely image lateral contrasts [START_REF] Dahlin | A Numerical Comparison of 2D Resistivity Imaging with Ten Electrode Arrays[END_REF]. Transverse profiles A1, A2 and A3 were acquired using 64 electrodes spaced every 4 m in the upper part of the mudslide. Transverse profiles C1 (80 electrodes, 4 m spacing) and C2 (48 electrodes, 5 m spacing) were acquired in the medium part of the mudslide. Finally, the longitudinal CA profile (64 electrodes, 5 m spacing) was acquired between transects C1 and A1. The raw data were inverted separately in 2D using the RES2DINV inversion software [START_REF] Loke | Rapid least-squares inversion of apparent resistivity pseudosections by a quasi-Newton method[END_REF], considering an L2-norm for optimisation. Derived resistivity images present RMS errors lower than 3% after 5 iterations.

These electrical images (fig. 3) show a clear contrast between the mudslide material with low resistivity values (less than 90 Ω.m) and the stable black marls bedrock with higher resistivity values (more than 150 Ω.m). These resistivity values are comparable to those obtained by [START_REF] Schmutz | Joint electrical and time domain electromagnetism (TDEM) data inversion applied to the Super Sauze earthflow[END_REF] from joint-inversion of VES and TDEM data, who found a resistivity range of 2 to 50 Ω.m for the active unit and more than 400 Ω.m for the substratum.

The increase of resistivity values with depth observed in the mudslide material can be explained by a decrease of the hydraulic conductivity with depth due to both the presence of water-saturated cracks in the topmost layer and compaction of the lowermost layer. On the eastern part of profiles C1 and C2, higher resistivity values (more than 700 Ω.m) are observed; they correspond to stable hillslopes formed of moraine deposits. These electrical tomographies correctly image the transverse and to a lesser degree the longitudinal thickness changes of the mudslide, underlying its complex bedrock topography.

In the medium part of the mudslide, the electrical images indicate a total thickness ranging from 24 m to less than 5 m along the C1 and C2 profiles; this geometry is consistent with the depth variations proposed by Malet & [START_REF] Maquaire | Black marl earthflows mobility and long-term seasonal dynamic in southeastern France[END_REF] for this section on the basis of geotechnical tests. In the upper part of the mudslide, a more or less constant thickness of 18 m is found along the A1 profile, while the A2 and A3 profiles indicate strong lateral changes due to the presence of in-situ buried bedrock crests. These profiles point out a deeper bedrock (more than 30 m) than in the medium part. Although geotechnical in this part of the mudslide are more scarce, the resistivity variations seem in accordance with the combined geomorphological-geotechnical interpretation suggested by [START_REF]Les 'glissements de type écoulement' dans les marnes noires des Alpes du Sud. Morphologie, fonctionnement et modélisation hydro-mécanique[END_REF]. As these tomographies were acquired in the autumn season, the surface formations present larger resistivity values probably due to dryer hydrological conditions. Finally, the longitudinal electrical image indicates smooth vertical variations, with a maximum depth reaching 18 m at the intersection with the C1 profile.

To summarize, the tomography profiles provided valuable and continuous information about the pseudo-3D geometry of the mudslide. These data will be used in zones lacking of geotechnical measurements for interpreting seismic noise interpretation.

H/V method Three H/V seismic noise profiles were performed on the mudslide (fig. 2). Two of them (C and B) were acquired in the transverse direction, along the C and B geotechnical crosssections, considering 15 m and 10 m spacing between each seismometer, respectively. A longitudinal profile (CA) was acquired between the A and C geotechnical cross-sections, with a 10 m spacing. In our experiments, we used six 3D Lennartz sensors (5 seconds), which gave flat responses in the [0.2-50 Hz] frequency range. They were connected to a CityShark TM II acquisition system developed for noise measurement [START_REF] Chatelain | CityShark: A user-friendly instrument dedicated to ambient noise (microtremor) recording for site and building response studies[END_REF]. Ambient vibration data were sampled at 200 Hz and recorded for 30 minutes. Among these 30 minutes, a maximum of short time windows (about 40 seconds) are selected through an anti-trigger process in order to select the more stable signal of noise ratio, ie. without transient highfrequency waves. Finally, Fast Fourier Transforms were processed for the three components and the spectral ratio was computed for each horizontal component (ie., H1/V and H2/V) as well as the quadratic average of the spectral ratio (H/V). Interesting recommendations for acquisition and processing tools dedicated to H/V measurements can be found in the conclusions of the SESAME European Research Project [2005]. To investigate complex and irregular structures, [START_REF] Uebayashi | Extrapolation of Irregular Subsurface Structures Using the Horizontal-to-Vertical Spectral Ratio of Long-Period Microtremors[END_REF] suggested orientating one component of the seismometer parallel to the structure variations because the frequency peak amplitude is sensitive to the orientation of the horizontal component. Therefore, on profiles CA and C the spectral ratio was computed using the E-W component, as the most important change is expected to occur along the longitudinal axis of the mudslide. On profile B, the spectral ratio was computed using the N-S components the geotechnical investigations indicate large lateral variations in the bedrock depth. On profile CA, a clearly distinguishable dominant frequency can be easily picked; this dominant frequency varies smoothly along the profile. For some points, higher frequencies exhibiting higher H/V amplitudes could have been wrongly picked (eg., like for point 7, with two major frequencies around 10 Hz and 15 Hz; but also lower frequencies at some points).

Even if the structure along this profile is 3D, the dominant frequency varies continuously and this feature can be explained by the smooth variations of the thickness along the profile, and by a well-adapted spatial sampling (10 m). In this case, no 3D effects significantly disturb both data acquisition and data processing, implying that surface waves propagation can be considered as 1D [START_REF] Bonnefoy-Claudet S | Nature du bruit de fond sismique : implications pour les études des effets de site[END_REF]]. On the contrary, it is clear that problems arise for profile B, where different resonance frequencies can be picked for a single point measurement, probably generated by different layers. In this case of large lateral thickness variations at a small-scale, the chosen spatial sampling (every 10 m) is too large to identify continuous variations of the suitable frequency. A blind frequency picking performed considering the maximum H/V amplitudes resulted in too large heterogeneities.

Consequently, we decided to pick two frequencies on some points, and propose a non-unique interpretation (fig. 5), considering the presence of several layers. To overcome this problem, a more adapted sampling scheme may improve the interpretation. In our case, the lowfrequencies appearing mainly on the flanks of the mudslide must be related to a deeper interface (probably linked with the presence of former coarse mudslide), which was identified on electrical images. Other points (11, for example), exhibited unexplained low frequency amplification, probably due to acquisition problems linked with coupling effects or local subsurface heterogeneities, disturbing the surface wave propagation. Profile C1 is a mix between the two previous examples. The observed variations are smoother, and the pickings appear realistic (fig. 5) except in the eastern part of the profile (from tests 1 to 5, where tests 1 to 3 are located outside of the mudslide). Again, this ambiguity must come from the presence of former coarse mudslide. Finally, the seismic noise measurements recorded for the network experiment (fig. 4d) exhibit consistent frequencies with those deduced from the profiles, underlying a smooth geometry in this part of the mudslide.

Figure 5 presents the interpretation of the picked frequencies in term of thickness (red points). The thickness was computed by using the formula f 0 =Vs/4Hs and considering a constant shear velocity Vs = 260 m.s -1 in the mudslide. This velocity was deduced from the surface waves and from the seismic noise network analyses (fig. 6, fig. 7). The presence of two peaks in some H/V ratios (fig. 4b, fig. 4c) resulted in two possible interpretations, although lower frequencies are expected to be due to the presence of deeper interfaces (former coarse mudslide), acquisition problems or local heterogeneity. The bedrock geometry was deduced from geotechnical data when available (black points), photogrammetric stereo-restitution of the topography before and after the mudslide [Weber and Herrman, 2000], and H/V interpretation. The surface topography changes between 1996 (when the geotechnical investigation was carried out) and 2005 (when the geophysical acquisition was carried out) were taken into account. Finally, the blue dashed line corresponds to the interpretation of electrical tomographies (fig. 3). The limit was adjusted using geotechnical measurements.

These results show that the interpretation of the picked frequency in term of thickness is particularly consistent with other measurements, even if the structure is 3D. However, it is clear that when H/V spectral ratios exhibit more than one peak in the interesting frequency range, interpretation is more doubtful and a spatial over-sampling is needed. Variability of the mudslide shear wave velocity can also explain the small differences between the known geometrical model and the estimated thickness. It should be noted that electrical interpretation is well consistent with the deduced interface on the bottom of the CA profile, but less on the C profile. These differences must be due to the lack of precision of smooth electrical tomography, particularly when lateral variability is present for the used Wenner configuration.

Seismic noise network

An array noise experiment was performed in the middle part of the C cross-section (fig. 2), consisting of three circle arrays (radius of 10, 25 and 50 m) each composed of 6 seismic stations. To compare the dispersion curve derived from these measurements, a longitudinal active seismic line was recorded along the CA profile (fig. 2) using 24 4.5 Hz-vertical geophones placed every 10 m.

Figure 6e displays the dispersion curve computed from the passive seismic noise arrays and associated error) and the semblance map of the energy of the active surface waves. It must be underlined that only two seismic noise arrays (radius of 10 and 25 m) were used (transition frequency around 7 Hz on the dispersion curve), the larger one (50 m radius) presenting no dispersion effect (certainly due to 3D effects for these wavelengths). These dispersion curves are well consistent and display the same variations except for low frequencies. This demonstrates that the seismic noise measurements are mainly composed of surface waves which is one of the major assumptions for seismic noise interpretation (with the 1D hypothesis).

The inversion results are displayed on figures 6c and 6d for the seismic noise and figure 6a and 6b for the active surface waves. During the inversion process, the H/V peak was added as a priori information only for the seismic noise inversion. On figures 6b and 6d, the experimental inverted dispersion curve computed from real data are superimposed to the models derived after inversion, the low RMS errors being presented in red. For both inversions, best models show S-waves velocity ranging between 260 and 300 m.s -1 for the topmost layer. They also show a well-defined thickness between 19-22 m for the noise and not well defined thickness between 16 and 20 m for the surface waves. All these results are consistent with other data acquired on this smooth area, which was densely imaged from electrical measurements and H/V data. It is noticeable that both results also showed thin contrasts inside the mudslide, which could be related to the observed superimposed units discussed before. The shear wave velocity of the bedrock is not so well retrieved. It varies between 600-700 m.s -1 for the surface waves and between 1100-1300 m.s -1 for the seismic noise. Considering the large uncertainty on the dispersion curve of the seismic noise at low frequencies, it may be reasonable to keep the velocity deduced from surface waves.

To summarize, combined seismic noise arrays were able (1) to derive consistent surface wave dispersion curves compared to those provided from active surface wave analysis, and

(2) to propose inversion models constrained with H/V information which retrieved precisely S-wave velocity and thickness of the mudslide. With lower frequencies (network radius >20m), thickness and S-wave velocity of the bedrock may have been more precisely investigated.

INVESTIGATION OF THE SAINT-GUILLAUME TRANSLATIONAL LANDSLIDE

Geological, geomorphological and geotechnical setting of the translational landslide

The Saint-Guillaume landslide is located in the Trièves basin (fig 1) where many clayey landslides have occurred in the past in the so-called varved clays; these clays are finely laminated glacio-lacustrine deposits dating from the Pleistocene (Wurmenien) period [START_REF] Jongmans | -Les argiles litées du Trièves (Isère), conditions de glissement de terrain et exemples de propriétés géotechniques[END_REF][START_REF] Van Asch | Hydrological triggering conditions of landslides in varved clays in the[END_REF]. The observed landslides present slip surfaces at different depths [START_REF] Jongmans | -Les argiles litées du Trièves (Isère), conditions de glissement de terrain et exemples de propriétés géotechniques[END_REF]Nieuvenhuis, 1991] from almost shallow ones (4 to 8 m) to more deeper ones (20 to 40 m).

The investigated landslide is a slow (1-5 cm.year -1 ) translational landslide affecting the small village of Saint-Guillaume. The geological basement is composed of Oxfordian marly limestone covered with 40 to 50 m of varved clays. The landslide is limited to the South by a limestone cliff overhanging a scree-covered hillslope (fig. 7). A umbilical zone of limestone is also visible to the East sub-dividing the clay formation in two parts. To the North the landslide is limited by the Gresse torrent which has incised a narrow channel in the varved clays. In the Western part of the landslide a geomorphological survey (geomorphological map, topographic control points) and a geotechnical investigation (three inclinometers, one piezometer) have been carried out in the late nineties. The boreholes have pointed out the existence of an interface between the uppermost varved clay and the marly limestone bedrock at 38.5 m, 61.7 m and 33.1 m depths at I1, I3 and I4 boreholes respectively (fig. 7). The inclinometers detected sometimes several slip surfaces inside the clay formation; the main slip surfaces were located at 34.5 m, 37.0 m, and 27.0 m depth, respectively. This monitoring system has been complemented since 2003 by geophysical investigations. Those are described in Garambois et al. (submitted). As a consequence, only a sum up of the main characteristics of the landslide is developed hereafter. As for the Super-Sauze mudslide, seismic noise measurements (H/V and seismic noise network) were tested (fig. 7). The comparison with Super-Sauze is interesting because Saint-Guillaume presents smoother bedrock geometry and thinner S-wave contrast.

H/V method

The H/V profile was carried out along an East-West direction perpendicular to the main displacement of the landslide. Measurements were made every 20 m, including in the village and on the marly limestone bedrock arising at the surface (tests 70 to 80). Figure 8a highlights the presence of two resonance frequencies, respectively around 1.3 Hz and 2 Hz. They are joined between tests 55 and 76 (high single frequency) and on the edges of the profiles (low single frequency). When the bedrock arises to the ground surface, both frequencies vanished.

Considering S-wave refraction [Garambois et al., 2006, submitted] and surface wave analysis (fig. 9), the S-wave velocity of the upper layer is around 260 m.s -1 . We consequently interpreted the higher frequency in term of thickness with this velocity (fig. 8b). The interface lies between 0 (where the bedrock reaches the surface) and 50 m. Black dots located on test 32 represent the known slip surface and bedrock depth in the I3 inclinometer. The lower frequency is more difficult to interpret. As it vanishes when bedrock reaches surface, it may correspond to the signature of the clay/marly limestone interface located at 61 m at inclinometer I3 (fig. 8b). For the frequency to depth conversion, we used a velocity profile as a function of depth, which was deduced from S-wave refractions analysis and surface waves analysis (fig. 9). Both showed that the undisturbed clays exhibit a velocity around 550 m/s.

Using an equivalent velocity (Vs equivalent = (Vs disturbed clays * H disturbed clays + Vs undisturbed clays * H undisturbed clays )/( H disturbed clays + H undisturbed clays )), the low frequency was picked and converted into depth, allowing to obtain an image of the bedrock geometry. The derived curve is relatively well consistent with the I3 deduced bedrock depth and remarkably with an electrical tomography image reaching 80 m depth [Garambois et al., 2006, submitted]. All the results suggest that the landslide develop first at the clay/bedrock interface when bedrock reaches the surface, and then within the clay layer (as confirmed by inclinometer monitoring). Compared to the Super-Sauze mudslide, frequency picking was easier certainly because the structures are less 3D and present less heterogeneity.

Seismic noise network

Seismic noise arrays, performed around inclinometer I3, are composed of three arrays, with radius of 20, 40 and 60 m (fig. 7). Again, this investigation was combined to an active seismic experiment using 24 4.5 Hz-vertical geophones. All data were processed in the same way than in the Super-Sauze investigation. Figure 9 presents the results derived from both passive and active seismic surveys. The frequency range of the dispersion curves largely differs depending on the method. Indeed, the passive method provided useful information in the [2.5-6.5 Hz] frequency range and the active method in the [4-12 Hz] frequency range. In the [4-6.5 Hz] frequency range, both dispersion curves are remarkably consistent, as displayed on figure 9c. This observation shows that the larger part of the energy contained in the seismic noise is made of surface waves. The inversion process was performed using the H/V constrain for the passive network.

Both best models (low RMS) are consistent with the geotechnical and geophysical data.

The S-wave velocity of the topmost layer is well constrained in both experiments, ranging from 260 to 280 m.s -1 , although seismic noise dispersion curve exhibited few high frequencies. It corresponds to the unstable clayey zone highly affected by deformation. Its thickness is also relatively well-defined, ranging from 31 to 34 m for the passive seismic noise method and from 28 to 30 m thick for the active method. The difference may arise from the 3D homogenisation property of the array, which integrates the information on a larger zone and includes variability in landslide thickness. Moreover, it must be noted that the surface wave acquisition was performed on the N-W edge of the array.

As discussed before, S-wave velocity varies around 550 m.s -1 (Vp=1800 m.s -1 ) in the stable part of clays, and reaches more than 800 m.s -1 (Vp > 2500 m.s -1 ) in the marly limestone bedrock. Figure 9 clearly outlines that both methods found best models displaying S-wave velocity around 600 m/s for the second layer (the stable clays). However, they were unable to detect and characterize the bedrock interface, although there is a large increase of Rayleigh velocity at low frequencies for the seismic noise network (but with a large uncertainty).

CONCLUSIONS

Two seismic noise experiments were performed on two landslides presenting different characteristics: (1) a mudslide characterized by abrupt 3D variations in the bedrock geometry and large S-wave velocity contrasts, and (2) a translational landslide where the slip surface geometry as well as the S-wave contrasts are smoother. H/V measurements showed their efficiency in characterizing the contact between the stable and unstable material for both landslides, as well as the bedrock interface for the translational landslide. Difficulties arise on the mudslide, as multiple resonance frequencies appeared. Some of them may be due to deeper interfaces, heterogeneities or bad coupling effects during the acquisition. To increase interpretation confidence, an adapted spatial sampling must be adapted to the 3D structure effect.

Inversions of dispersion curves obtained from seismic noise arrays on both sites were compared to geotechnical data, as well as to results provided by active surface wave investigations. First, a clear correlation between active and seismic dispersion curves indicated that in both cases seismic noise was mainly composed of surfaces waves. Second, large arrays are not always efficient. For the Super-Sauze mudslide, the larger array enabled to record consistent dispersive waves at low frequencies.

In soft-rock landslides, slip surfaces appear to generate large S-wave velocity contrasts that seismic noise methods are able to detect and characterize properly. Consequently, combined to theoretical studies, seismic noise methods may be of high interest to identify and map slip surfaces in 3D.

AKNOWLEDGMENTS

Figures

  Figures 4a, 4b and 4c present H/V spectral ratios calculated in the [0.2-20 Hz] frequency

  This work was supported by grants from the French Ministry of Research within the ACI project SAMOA 'Surveillance et Auscultation de MOuvements gravitaires Alpins' (Coordinators: C. Delacourt, O. Maquaire and D. Amitrano) and the ACI project GACH2C 'Glissements Alpins à Contrôle Hydrologique et Changement Climatique' (Coordinators: O. Maquaire and J.-P. Malet). The investigation carried out at Saint-Guillaume was supported by grants from the Conseil Général de l'Isère within a 'Pôle Grenoblois des Risques Naturels' project.

FIGURE CAPTIONS Figure 1 :

 CAPTIONS1 FIGURE CAPTIONS

Figure 2 :

 2 Figure 2: 3D topography image of the Super-Sauze mudslide and locations of the geophysical

Figure 3 :

 3 Figure 3: Electrical tomography images derived after inversion of data acquired using a

Figure 4 :

 4 Figure 4: H/V and seismic noise network results obtained at the Super-Sauze mudslide along

Figure 5 :

 5 Figure 5: Interpretation of H/V picked frequencies of the Super-Sauze mudslide considering a mean S-wave velocity of 260 m.s -1 . It was compared to geotechnical and electrical data. The

Figure 6 :

 6 Figure 6: Inversion results of the dispersion curve obtained from the seismic noise network

Figure 7 :

 7 Figure 7: Aerial photograph of the Saint-Guillaume landslide, including locations of the three

Figure 8 :

 8 Figure 8: H/V results obtained at Saint-Guillaume landslide (a) and interpretation of the

Figure 9 :Figure 1 :

 91 Figure 9: Inversion results of the dispersion curve obtained from the seismic noise network

Figure 2 :

 2 Figure 2: Image 3D de la topographie du glissement-coulée de Super-Sauze et positionnement

Figure 3 :

 3 Figure 3: Image de tomographies électrique déduites après inversion de données acquis en

Figure 4 :

 4 Figure 4: Résultats des mesures H/V obtenues sur le glissement-coulée de Super-Sauze le

Figure 5 :

 5 Figure 5: Interprétation des fréquences pointées des mesures H/V sur le glissement-coulée de Super-Sauze considérant une vitesse de 260 m.s -1 . Ces interprétations sont comparées aux

Figure 6 :

 6 Figure6: Résultats de l'inversion de la courbe de dispersion du réseau de bruit de fond

Figure 7 :

 7 Figure 7: Photographie aérienne du glissement de Saint-Guillaume avec la localisation des

Figure 8 :

 8 Figure 8: Résultats du H/V mesuré sur le glissement de Saint-Guillaume (a) et interprétation

Figure 9 :

 9 Figure9: Résultats de l'inversion de la courbe de dispersion du réseau de bruit de fond

  Figure 1

installer sur site, afin de cartographier des contrastes de vitesse d'onde S (surface de glissement) et de (2) de mesures de bruit de fond réseau, plus délicate et complexe à déployer sur site et à interpréter, mais qui permet d'accéder à des profils de vitesses d'ondes S en fonction de la profondeur. Les comparaisons entre nos investigations géophysiques et les sondages géotechniques prouvent l'applicabilité des méthodes géophysiques passives dans des environnements 3D, mais indiquent également certaines limites. En effet, l'interprétation des données peut s'avérer difficile dans des terrains hétérogènes et à forte rugosité.

We express our gratitude to the RTM38 and particularly to Mrs. Catherine Moulin for providing geotechnical data on the Saint-Guillaume landslide. We also thank all colleagues who helped us during the field investigation, as well as the people from the city office of Saint-Guillaume.


Germán Leiva
email: leiva@lri.fr

Michel Beaudouin-Lafon

Montage: A Video Prototyping System to Reduce Re-Shooting and Increase Re-Usability

Keywords: •Human-centered computing → Systems Video prototyping, Paper prototyping, Wizard-of-Oz

Figure 1: Chroma mode: the UserCam captures the context (a) and the WizardCam captures the paper prototype (b); Both live-stream video to the Canvas. Designers draw digital sketches over the streamed paper prototype to represent the interface (c).

In the Canvas, the green screen is replaced with a perspective transformation of the interface to create the final composition (d).

INTRODUCTION

Pen-and-paper is widely used when designing and communicating interactive systems, especially for quick prototyping [START_REF] Beaudouin-Lafon | Prototyping tools and techniques[END_REF]. Sketching on paper has well-known benefits [START_REF] Buxton | Sketching User Experiences: getting the design right and the right design[END_REF]: it does not require technical skills, is inexpensive -in time and moneyand, as a consequence, is easy to throw away. Paper excels in representing static visual properties and physical transformations such as moving paper elements [START_REF] Greenberg | Sketching User Experiences: The Workbook[END_REF]. However, paper makes it difficult or impossible to create dynamic transformations that continuously re-shape or modify the design elements, such as re-sizing or stretching elements or modifying colors and strokes in response to continuous user input.

In a paper prototyping session [START_REF] Snyder | Paper prototyping: The fast and easy way to design and refine user interfaces[END_REF], a user interacts with the prototype, while one or more designers, or wizards, play the role of the computer. When the design changes or when exploring variants, instead of modifying the existing paper representations, they are thrown away and new ones are quickly created. The user can simulate the interaction over the paper prototype to communicate a rough idea, such as tapping with a finger to simulate a mouse click. The Wizard of Oz (WOz) technique [START_REF] Green | The Rapid Development of User Interfaces: Experience with the Wizard of OZ Method[END_REF] can create more realistic prototypes when the wizards conceal their actions. The WOz technique is not limited to paper, and can be used, e.g., with a video projector to create a more compelling setup.

Video prototyping [START_REF] Mackay | Video Prototyping: a technique for developing hypermedia systems[END_REF][START_REF] Mackay | Using Video to Support Interaction Design[END_REF][START_REF] Mackay | Video brainstorming and prototyping: techniques for participatory design[END_REF] combines paper and video with the WOz technique to persist, communicate, and reflect about the interaction design. Videos can range from inexpensive recording of a traditional paper prototyping session [START_REF] Rettig | Prototyping for tiny fingers[END_REF] to a high-budget video prototype [START_REF] Tognazzini | The "Starfire" video prototype project[END_REF] requiring specialized equipment [START_REF] Bardram | Virtual video prototyping of pervasive healthcare systems[END_REF]. Video provides additional prototyping capabilities, such as jump cuts for simple appear/disappear effects or adding shots for contextualizing the user and the system within a story. However, using video together with paper hinders some of the benefits of using paper alone. Depending on the audience of the video, the wizard's trickery might need to be concealed, increasing the time and cost to produce a prototype. Introducing changes in the paper prototype creates inconsistencies with previously recorded scenes, leaving designers with three choices: sacrificing the consistency throughout the video, fixing the affected scenes in post-production editing, or re-shooting all the affected scenes.

Our goal is to provide better support for video prototyping in an integrated way to avoid inconsistencies [START_REF] Maudet | Design Breakdowns: Designer-Developer Gaps in Representing and Interpreting Interactive Systems[END_REF]. How can we help designers persist their prototyping iterations consistently, with minimum post-production editing and re-shooting? We introduce Montage, a distributed mobile system supporting iterative video prototyping in the early stages of design. After reviewing related work, we describe Montage through a scenario that compares traditional video prototyping techniques with the enhanced approach using Montage. We then discuss prototyping opportunities with Montage for different interaction styles, including multi-modal interaction and augmented reality. Finally we describe the technical implementation of Montage, its current limitations, and future work.

RELATED WORK

In recent years many academic and commercial tools have emerged to support the prototyping of graphical user interfaces [START_REF] Rocha | A Comparative Study of Milestones for Featuring GUI Prototyping Tools[END_REF]. While pen-and-paper is one of "the most widely used prototyping medium" [START_REF] Carter | How is User Interface Prototyping Really Done in Practice? A Survey of User Interface Designers[END_REF], some researchers argue that informal computer-based tools might better support the prototyping of interactive behaviors [START_REF] Bailey | Are informal tools better?: comparing DEMAIS, pencil and paper, and authorware for early multimedia design[END_REF]. For example, SILK [START_REF] Landay | Interactive Sketching for the Early Stages of User Interface Design[END_REF] lets designers sketch interfaces with a digital stylus to generate functional widgets, while Monet [START_REF] Li | Informal prototyping of continuous graphical interactions by demonstration[END_REF] expands this functionality to prototype continuous interactions by demonstration. Our goal is not to replace paper or impose an exclusive use of digital tools. Instead, Montage augments physical prototyping by extending the traditional paper-based techniques.

Other researchers have proposed tools that explicitly support the Wizard of Oz (WOz) technique. Some examples include WozARd for prototyping location-aware mobile augmented reality [START_REF] Alce | WozARd: A Wizard of Oz Tool for Mobile AR[END_REF], SketchWizard for pen-based interfaces [START_REF] Davis | SketchWizard: Wizard of Oz Prototyping of Pen-Based User Interfaces[END_REF], and Suede for speech-based interfaces [START_REF] Scott | Suede: A Wizard of Oz Prototyping Tool for Speech User Interfaces[END_REF]. Apparition [START_REF] Walter S Lasecki | Apparition: Crowdsourced User Interfaces That Come To Life As You Sketch Them[END_REF] helps designers prototype web-based systems in real time by crowdsourcing part of the wizard's trickery. Unlike these, Montage is not dedicated to a particular type of interface, making it a more generic tool for a variety of situations. Furthermore, the WOz technique has several limitations, such as the wizard's stress and fatigue, the lack of reuse of the prototypes, and the delays and time lag between user actions and system response [START_REF] Sören | Perspectives on Ozlab in the cloud: A literature review of tools supporting Wizard-of-Oz experimentation, including an historical overview of 1971-2013 and notes on methodological issues and supporting generic tools[END_REF]. Montage supports live WOz but overcomes these shortcomings by using recorded and composable videos. Composition enables reuse while recording helps reduce timing and fatigue issues, e.g. wizards can pause and resume recording as needed.

We share similar goals with DART [START_REF] Macintyre | DART: A Toolkit for Rapid Design Exploration of Augmented Reality Experiences Blair[END_REF]: supporting early design stages and recording synchronized data. DART needs code for custom behaviors, but "interviewees consistently expressed a desire for a tool to support prototyping without coding" [START_REF] Gandy | Designer's augmented reality toolkit, ten years later[END_REF]. Unlike DART, Montage targets lower fidelity prototypes, does not require coding and accommodates other use cases besides augmented reality.

Montage is close to RPPT (Remote Paper Prototype Testing) [START_REF] Chen | Remote Paper Prototype Testing[END_REF] but serves a different purpose: RPPT is used to run live testing sessions with real users while Montage helps create reusable video prototypes with designers and explore alternatives. Like RPPT, Montage supports live streaming of paper prototypes. But Montage also persists the video prototype and lets designers modify the design after recording, e.g. by using time manipulation (rewind, pause, fast forward) or by composing different alternatives designs.

Commercial tools evolved from the graphic design tradition, starting from sketching tools but currently focusing on "pixel perfect" designs with graphic-authoring tools such as Adobe Illustrator or Photoshop. However, most of these tools do not target early-stage design as they focus on the final look [START_REF] Bohemian | Sketch[END_REF] rather than the feel. The few tools that support nonstandard behaviors require visual [START_REF] Facebook | [END_REF] or textual [START_REF] Framer | Framer[END_REF] programming skills. Lee et al. [START_REF] Lee | SketchExpress: Remixing Animations for More Effective Crowd-Powered Prototyping of Interactive Interfaces[END_REF] observes that much of the interactive behavior remains as textual descriptions due to the cost of creating dynamic prototypes, even for professionals. Some tools extend traditional graphic authoring to support animations and effects, such as Flinto [START_REF] Flinto | Flinto[END_REF], but they ignore the role of user inputs and contexts of use. Only a handful of commercial tools support informal early-stage prototyping, e.g. by using paper-in-screen techniques [START_REF] Bolchini | Paper in Screen" Prototyping: An Agile Technique to Anticipate the Mobile Experience[END_REF]. For example, POP [30] lets designers create simple screen-flows by connecting pictures of paper prototypes through digitally defined hotspots. However, this only supports discrete actions, not dynamic interactions.

To solve these issues, many designers use presentation software, such as Keynote or Powerpoint, to mimic dynamic interactions [START_REF]Keynotopia[END_REF]. While suitable for some use cases, e.g. WIMP and mobile apps, their pre-defined animations target effects and transitions among slides, covering a tiny subset of all the available interaction styles. Professional designers also use video editing software, such as Adobe After Effects, to prototype the look of continuous interactions with high-fidelity videos. Luciani et al. [START_REF] Danwei | Empowering Non-Designers Through Animation-based Sketching[END_REF] use animation-based sketching techniques with professional editing tools, such as Adobe Premiere. However, current approaches to video editing are complex and time-consuming, which conflicts with the goals of early-stage prototyping. VideoSketches [START_REF] Zimmerman | Video Sketches: Exploring Pervasive Computing Interaction Designs[END_REF] uses photos instead of videos to avoid the high cost and production issues of creating video scenarios. Dhillon et al. [START_REF] Dhillon | Visual Fidelity of Video Prototypes and User Feedback: A Case Study[END_REF] have found no differences in the quality of feedback between a low-fidelity and a high-fidelity video. This supports the low-fidelity approach of Montage, based on freehand digital sketches and paper props. Montage directly supports an inexpensive animation-based sketching process, accessible to designers without video editing knowledge.

The benefits of low-fidelity video as a design tool have been investigated for a long time [START_REF] Mackay | Video: Data for Studying Human-Computer Interaction[END_REF]. According to Greenberg et al., "design is putting things in context" [START_REF] Greenberg | The Narrative Storyboard Telling a story about use and context over time[END_REF]. Montage contextualizes the design by encouraging designers to be useractors when demonstrating the prototype in a scenario [START_REF] Mackay | Video artifacts for design: bridging the Gap between abstraction and detail[END_REF].

In summary, current commercial tools create refined prototypes, more appropriate for mid/late stages of the design, while early-stage tools lack features to explore the details of continuous interaction. Montage fills this gap in the design space of prototyping tools: It enables the expression of highly dynamic interfaces in early low-fidelity video prototypes which can be recorded and modified without a need for post-production.

MONTAGE

Montage is composed of a central device -the Canvasconnected to two mobile devices -UserCam and WizardCamwith video streaming and recording capabilities. These devices, typically phones or tablets, are used as remote cameras. They stream, either in parallel or independently, the context of use where the user could interact with the prototype and the prototyped user interface itself. The Canvas lets designers organize and compose the video segments, and augment them with digital drawings that can be re-shaped and modified. Interaction designers can compose, draw and modify the prototype during rehearsal, during recording, or after filming. Montage focuses on low-budget video recording but provides designers with features currently only available in high-budget video prototyping, such as layering and tracking. Interaction designers can start with traditional paper prototyping and progressively move towards modifiable and re-usable digital representations without the need for professional video editing software.

Montage targets interactions that require continuous feedback, such as scaling a picture with a pinch or selecting objects with a lasso, which are often challenging to perform with traditional paper and video prototyping. We first illustrate the approaches and challenges of prototyping continuous feedback with traditional video prototyping, and then present an enhanced approach using Mirror, a mode of Montage that mixes streamed physical elements (such as a paper prototype) captured by a camera, with digital elements created remotely by a wizard. Finally, we present Montage Chroma to reduce re-shooting while exploring alternative designs.

Prototyping with traditional paper and video techniques

Imagine a group of designers prototyping an interaction technique with dynamic guides, similar to OctoPocus [START_REF] Bau | OctoPocus: A Dynamic Guide for Learning Gesture-based Command Sets[END_REF]. Oc-toPocus provides continuous feedback (inking) and feedforward (potential options) of the gestures as a user performs them 1 . The designers want to illustrate the use of this technique in the office, when interacting with the profile picture of a friend on a phone: when dwelling on the picture, OctoPocus should show three gestures for calling, messaging or finding directions to the friend. The designers print an image to use as the profile picture and attach it to the screen of a phone, used as a theatrical prop, to contextualize the prototyped interaction. The user-actor draws on the profile picture to mimic the continuous feedback of a gesture. She uses a black pen hidden as well as possible in his palm, while a wizard draws the feedforward, i.e. three colored curved lines. This approach to prototyping continuous feedback and feedforward has three main drawbacks:

• The hand and pen of the wizard appear in the video;

• The profile picture has drawings on it that might not be easy to erase, so in case of mistakes or changes, it requires a new picture or at least recording the whole video again; and • Illustrating the use of the same technique in different contexts (on the profile picture of other friends, or in a completely different scenario) also requires re-shooting.

The designers take a different approach to avoid these problems. They create four sketches with transparent paper to represent the different stages of the OctoPocus interaction (Figure 2): They plan to reveal the feedforward and feedback progressively by overlaying the sketches on top of the profile picture, one sketch at a time. They use a mobile device on a tripod to record a rough stop-motion video of the interaction.

With this approach, the designers reduce the presence of the wizard in the video, as they place the sketches on top of the profile picture in-between the stop-motion takes. Because the sketches are drawn over transparent paper instead of the profile picture, the designers can reuse their prototype props to illustrate other contexts of use. Nevertheless, this approach also comes with limitations and drawbacks:

• While it is possible to reuse the sketches in other contexts, the whole interaction needs to be re-shot; • A sequence of four sketches will poorly communicate the highly continuous nature of the interaction; and • Making a stop-motion video shifts the designers' attention from experiencing and reflecting on their design to coordinating sequences of extremely brief video shots.

A third approach is to use video editing software instead of paper sketches to add a digital overlay with the user interface on top of a previously recorded shot of the user actions. This approach has the disadvantage of creating a disruptive context switch, from a design session that does not require specialized skills to a video editing session requiring trained editors. Also, with paper prototyping the user interface is partially hidden by the user's hands, so a simple digital overlay will not produce the same effect. Only an experienced video editor could sim- In summary, with current approaches to video prototyping, designers struggle to represent continuous feedback and to reuse prototype props and previously captured interactions.

The tools that address these problems require video editing skills and extra effort in post-production, interrupting the flow of the design process. We want to better support video prototyping without disrupting the design process nor requiring specialized video editing skills.

Prototyping continuous feedback with Montage Mirror

Montage Mirror mixes physical elements captured by a Wizard-Cam (Figure 3a and 3b), with digital sketches drawn remotely in the Canvas (Figure 3d). The user-actor's phone displays a video stream of the paper prototype combined with the digital sketches -the interface. As the user-actor interacts with the phone, the wizards provide live feedback by editing the digital sketches on the Canvas or by manipulating the paper prototype captured by the WizardCam.

For example, to prototype OctoPocus, the user-actor sees the profile picture on his phone, captured by the WizardCam. As she performs a gesture on the screen, she sees the feedback and feedforward sketched remotely by the wizard on the Canvas. In this way, the user-actor can experience the prototyped interaction without the hands of the wizard getting in the way. The UserCam captures the interaction over the interface and the context of use to create the final video prototype.

Designers can animate changes in position, size, rotation angle, color, and thickness of the digital sketches without the tedious coordination required by stop-motion videos. Digital sketches can be grouped to create compound objects that have a semantic meaning in the story. Moreover, thanks to the Wiz-ardCam stream, traditional paper prototyping techniques are still available if necessary: physical sketches and props added to the paper prototype are directly streamed to the user-actor's phone. For example, after the user-actor performs a gesture with OctoPocus, the wizard can add a sticky note with the text "Calling Barney" on top of the profile picture.

Montage Mirror augments video prototyping with live digital sketches. In the Canvas, designers use the stylus to draw sketches and perform simple actions, such as pressing a button. Designers can move, resize and rotate sketches with the standard pan, pinch and rotate gestures. Unlike stop-motion videos, digital sketches allow prototyping continuous feedback interactions that look fluid and allows designers to focus on the design process instead of coordinating complex wizard actions. For example, to prototype the drawing of a question mark and the inking feedback, the wizard draws at the same time that the user-actor is gesturing. The designer rewinds the recorded video to the point where she wants the dynamic guides to appear and draws them. After pressing play, she uses a slider of the sketch interface to make the stroke progressively disappear as the video plays (Figure 4).

Mirror mode supports the prototyping of dynamic interfaces and continuous feedback. Nevertheless, it still requires reshooting when exploring alternative designs or contexts, e.g., showing OctoPocus on something else than a mobile phone. Designers have to record the whole video again even for small changes, such as changing the color of the dynamic guides.

Montage Chroma: Reusing captured interactions

To help designers reuse previously captured interactions and reduce re-shooting, the Chroma mode takes advantage of a well-known video editing technique called chroma key compositing. With chroma keying, the subject is recorded in front of a solid background color, generally green or blue, and this background is replaced in post-production with the desired content. This technique is commonly used by weather presenters on television, to replace a green background with an animated map with weather information. In our example, the user drawing a question mark is recorded over a phone showing a green screen, which is later replaced with the prototype interface. Achieving a clean chroma keying requires special attention to proper lighting conditions and using the right shade of green. However, we are not concerned in achieving a perfect result during an early-stage low-fidelity prototype. We can also use a different color than green, as long as it is distinct enough from the rest of the scene, by selecting it in the video feed with Montage's color picker.

In order to replace only the portion of the screen that contains the interface, we display a green screen on the user-actor's phone. The UserCam records the final video prototype, but in Chroma mode Montage also tracks the four corners of the green screen and sends this data to the Canvas. Then, the Canvas performs a perspective transformation of the current frame of the interface, and replaces the green area with the transformed interface. Montage Chroma not only performs this composition in post-production, i.e. after recording, but also during recording, in the final composition live preview.

Designers simply need to rewind the recorded video to add new sketches or modify existing ones. They can draw or modify the The setup of the system in Chroma mode (Figure 1) has just one difference from the setup in Mirror mode. The UserCam still captures the context but the phone now shows a green screen (Figure 1a). The final composition preview in the Canvas shows the chroma keyed result, positioning the interface correctly under the user's hands and following the phone's boundaries. When the designers modify the paper prototype or the digital sketches, i.e. add, remove, move, rotate, scale, or color change the sketches, Montage Chroma shows these modifications immediately in the final composition live preview, but not on the actual phone.

When possible, we recommend using Montage Mirror during rehearsal and Montage Chroma during recording. If the interface is to be placed on a screen-based device with streaming capabilities, using Montage Mirror lets the user-actor experience the prototype directly. During recording, using Montage Chroma allows to create composable video segments and lets the interface and the context to be changed independently.

Montage Chroma provides a "user overlay" to assist wizards sketch in relation with user inputs. For example, when the user-actor places a finger over the green screen, the wizard can see a translucent image of this finger over the drawing area of the Canvas; this helps wizards better coordinate spatially and temporally the drawings with respect to the user inputs. Montage uses the inverse perspective transformation of the green screen to correct the placement of the overlay.

Exploring design alternatives and multiple contexts of use

With chroma keying, the recorded interface videos and context videos can be changed independently. This flexibility reduces the cost of exploring different design alternatives and multiple contexts of use. For example, once an interface video of the OctoPocus technique is prototyped, it can be embedded in multiple contexts: different videos can show the user-actor using OctoPocus in the metro, in a park or at a party without having to re-shoot the interaction technique. The other way around is also possible: Several alternative designs of the interface can be embedded in the same context, with different videos showing the original context of the actor-user in his office using OctoPocus on a social media profile, an email client or the camera app.

Besides recording with the UserCam in different places, i.e. in a park or an office, the context can be changed by using a different device. Montage Chroma works with any device that can display a solid color in a rectangular frame, such as watches, phones, tablets, laptops and even wall-size displays, enabling designers to explore multiple display alternatives.

Supporting multiple interaction styles

Montage Chroma is not limited to displays such as a phone's screen. Designers can video prototype over other rectangular surfaces, such as boxes, books and whiteboards with a solid color. We can use Montage to prototype gesture-based interactions over a green sticky note or a t-shirt stamp. This allows the exploration of stationary as well as mobile contexts, e.g., sitting in front of an interactive table or walking with a phone.

Montage's digital sketches can depict 2D widgets common in WIMP interaction such as buttons, sliders and menus. Toggling the visibility of sketches on or off (Figure 4) at precise moments in the video is ideal for prototyping interactive transitions of the interface states, e.g. idle/hover/press states of a button or the screen-flow of a mobile app. Static sketches can depict discrete feedback, e.g. adding an object after pressing a button, while animated sketches can depict continuous feedback, e.g. inking, dragging or resizing with a pinch.

Montage also supports prototyping interactions that involve indirect input devices. By using a green screen on a laptop's display we can still see the mouse cursor, facilitating the positioning of interface elements. For example, to prototype a marking menu, we create a simple paper prototype of the menu. When the user clicks, we pause recording and introduce the paper prototype under the WizardCam. We resume recording and when the user moves, the wizard adds digital sketches to illustrate the feedback. Finally, when the user selects an item, the wizard highlights the corresponding item and modifies the paper prototype to show the response of the system.

With Montage we can even prototype interactions that use the spatial relationship between the devices and the users, such as Proxemic Interaction [START_REF] Greenberg | Proxemic Interactions: The New Ubicomp? interactions[END_REF]. For example, a user can walk closer or farther away from a device tracking her location, while the wizard manipulates the sketches to react to the user's position.

Prototyping multimodal interfaces, e.g., voice interaction and body movement, is possible with Montage. For example, to re-create the foundational Put-that-there interaction [START_REF] Bolt | Put-that-there[END_REF], both cameras record video and audio so that designers can enact the voice interactions that will be recorded. After the actor utters a voice command, the wizard pauses the recording, adds the necessary digital sketches and resumes recording. The video can then be modified, without re-shooting, to transition from paper to digital sketches or to add more details, such as the onscreen cursor. In more complex scenarios, the designers can sketch annotations on the context to indicate the user's voice commands or the system's audio responses, or to represent haptic feedback from the system, such as vibrations.

Video prototyping augmented reality systems is also easy with Montage. The designer attaches the UserCam to a headset, simulating the use of smart-glasses. With this setup, the useractor has his hands free to interact with the overlaid images created by the wizard. In many cases, there is no need to use Chroma mode because the interface elements are overlaid over the camera feed. For example, to prototype a menu that follows the user's hand, the wizard only needs to sketch over the context and move the sketches to follow the hand's movements.

The final video prototype will show the interaction from the point of view of the user-actor, i.e. the UserCam.

IMPLEMENTATION

Montage currently runs on iOS version 11.2. In our preferred setup, the Canvas runs on an iPad Pro 12.9 inches (2nd generation) with an Apple Pencil stylus. Generally, the UserCam runs on an iPhone 6S and the WizardCam on an iPad Mini 3. Other wireless devices are also suitable as and mirrors. We tested Montage Mirror with an Apple Watch 1st gen. (42mm case) and a MacBook Pro (13-inch, 2015).

We use AVFoundation [2] to capture video, intercept frame buffers, and create movie files. The frame buffers are processed with Core Image [START_REF]Apple Developer Documentation, Core Image[END_REF] to clean the images before detecting rectangular areas, to perform perspective and correction transformations, and to execute the chroma keying.

We use a zero-configuration network where the Canvas acts as a server browsing for peers that automatically connect to the system. Each camera records its own high quality movie, currently 1280x720 pixels. However, the video stream is sent at a lower quality (480x360 pixels) to maintain an acceptable latency during rehearsal and recording (M=180ms, SD=60ms).

The devices' clocks are synchronized to start, pause, and end the recording at the same time. Due to delays introduced by the wireless connection, we created a protocol to let the devices synchronize: When the designer presses Record on the Canvas the screen displays a "3, 2, 1, go" animation. This delay lets devices prepare for recording and synchronize their capture start time. We use the same mechanism when the designer resumes the recording after pausing.

In order to create a movie combining the dynamic sketches with the captured video, we save the designers' inputs during the manipulation of the digital sketches. We use this information to create keyframe animations at different points of the video playback. We added a synchronization layer on top of both to link these animated sketches with the underlining movie player. This new layer coordinates the animation playback with the movie file playback.

LIMITATIONS

We have observed that Chroma mode works best with flat surfaces, and rectangle tracking works poorly with flexible or shape-changing surfaces. Also, excessive user occlusion can prevent proper screen tracking. As a workaround, when the device is not moving, designers can lock the last tracked rectangle. Montage Chroma can also replace any solid-color area, regardless of its shape, with the interface. However, without position tracking, the perspective transformation of the interface is lost, resulting in a "naive" chroma keying.

One drawback of chroma keying is that the user-actor interacts with a green screen, not the final prototype. Using Mirror mode during rehearsal mitigates this problem. In Chroma mode, the user-actor should see the Canvas in order to monitor the state of the interface in relation with his inputs.

Finally, Montage only supports interaction styles that can be mimicked with video. Currently, we cannot illustrate complete immersive virtual worlds, e.g., VR applications or 3D games. However, Montage can still video prototype particular aspects of these examples, such as hand tracking.

CONCLUSION AND FUTURE WORK

Current approaches to video prototyping make it difficult to represent continuous feedback and reuse previously captured interactions. The tools that address these problems require video editing skills and extra effort in post-production, interrupting the flow of the design process. Therefore we need to better support video prototyping without disrupting the design process nor requiring specialized video editing skills.

We presented Montage, a distributed mobile system that supports video prototyping in the early stages of design. Our technical contribution is a novel tool integrating multiple live video streams, screen tracking, chroma keying, digital sketches and physical prototyping in one fully mobile video prototyping system. While these individual techniques are not new, Montage combines them in a novel way to support an enhanced video prototyping process: rehearsal with Mirror mode and recording with Chroma mode. Montage Mirror augments video prototypes with remote digital sketches, while Montage Chroma supports the reuse of previously recorded videos to explore alternative interfaces and contexts of use. We described a scenario that demonstrates the limitations of traditional paper and video techniques, and showed how Montage addresses them. Finally, we illustrated how Montage can prototype a variety of interaction styles, including touch-based (OctoPocus), WIMP (marking menu), AR (on-hand menu), multimodal (Putthat-there), and ubiquitous computing (Proxemic Interaction).

Future work involves evaluating Montage with professional interaction designers, improving screen tracking and exploring the reuse of video prototypes beyond early-stage design, e.g. by supporting the transition to high-fidelity prototypes.

Figure 2 .

 2 Figure 2. OctoPocus with traditional video prototyping. The designers create a rough stop-motion movie with only four stages of the interface, resulting in a poor representation of the dynamic interaction.

Figure 3 .

 3 Figure 3. Montage Mirror: the WizardCam live streams to both, the Canvas (a) and to the prototyped device (b) in the context. The UserCam only streams to the Canvas (c). Finally, the Canvas sends the sketches to the prototyped device to complete the mirroring of the interface

Figure 4 .

 4 Figure 4. The Canvas sketching interface: The final composition (left) and the interface (right) show the "user overlay". Both sides have a list of sketches and animation controls at the bottom. The in/out buttons make the selected sketches appear/disappear. The sliders control the stroke-start, now at 0%, and the stroke-end, now at 100%.

See https://vimeo.com/2116172

ACKNOWLEDGMENTS

This work was partially supported by European Research Council (ERC) grants n°321135 CREATIV: Creating Co-Adaptive Human-Computer Partnerships, and n°695464 ONE: Unified Principles of Interaction. We thank Wendy Mackay and the ex)situ team for their help and support, and Carla Griggio for her multiple contributions to this work.