Laurent Bigarré

Georges Plassiart

Claire De Boisseson

Laurane Pallandre

Françoise Pozet

Yannick Ledore

Pascal Fontaine

François Lieffrig

Claire De Boisséson

Yannick Ledoré

Molecular investigations of outbreaks of Perch perhabdovirus infections in pike-perch

Keywords: Pike-perch, Sander lucioperca, Perch rhabdovirus, Percidae, virus, epizooty

Introduction __________________________________________________________________

The genus Perhabdovirus regroups 3 viral species pathogenic to fish: Perch perhabdovirus (e.g. perch rhabdovirus, PRV), Sea trout perhabdovirus (e.g. lake trout rhabdovirus, LTRV) and Anguillid perhadovirus (e.g. eel virus European X, EVEX) (www. talk.ictvon line. org). To date, Anguillid perhabdo virus has been found only in eels, whereas PRV and LTRV have been detected in various fish species during clinical episodes in farms or experimental facilities in Europe [START_REF] Betts | Emerging vesiculo-type virus infections of freshwater fishes in Europe[END_REF][START_REF] Talbi | Genetic diversity of perch rhabdo -viruses isolates based on the nucleoprotein and glycoprotein genes[END_REF][START_REF] Gadd | Characterization of perch rhabdovirus (PRV) in farmed grayling Thymallus thymallus[END_REF]. In particular, in the last 3 decades, wild and farmed percids (European perch Perca fluviatilis, pike-perch Sander lucioperca) have been affected by PRV or LTRV in different countries, such as France, Norway, Ireland and Switzerland [START_REF] Dorson | A rhabdovirus pathogenic for perch, Perca fluviatilis L.: isolation and preliminary study[END_REF][START_REF] Nougayrède | Isolation of a rhabdovirus from the pike-perch Stizo stedion lucioperca (L.1358)[END_REF][START_REF] Dannevig | The first isolation of a rhabdovirus from perch (Perca fluviatilis) in Norway[END_REF][START_REF] Rodger | Diseases and health management in perch farming[END_REF][START_REF] Ruane | Genetic diversity and associated pathology of rhabdovirus infections in farmed and wild perch Perca fluviatilis in Ireland[END_REF][START_REF] Wahli | First isolation of a rhabdo -virus from perch Perca fluviatilis in Switzerland[END_REF]. The disease has been reported in fry and adults, with high mortality rates in some cases. Symptoms ob served in adults are variable. Fish often exhibit ab normal swimming behavior and lethargy, as well as hemorrhaging at the base of the fins. Histopathology of affected juvenile perch reveals necrotic cells in the liver, spleen hematopoietic tissue and intestinal lamina propria as well as congestion in the central nervous tissue. PRV can be isolated by cell culture, starting from ground organs, e.g. anterior kidney, liver, spleen and brain of juveniles [START_REF] Dorson | A rhabdovirus pathogenic for perch, Perca fluviatilis L.: isolation and preliminary study[END_REF].

The diagnostic of PRV is usually performed using cell culture confirmed by an immunofluorescence antibody test or using a generic RT-PCR starting from RNA extracted from the culture supernatant [START_REF] Talbi | Genetic diversity of perch rhabdo -viruses isolates based on the nucleoprotein and glycoprotein genes[END_REF]). To our knowledge, to date, there is no PCR assay using total RNA from organs.

Perhabdoviruses have an ssRNA genome of about 11.5 kb encoding 5 genes [START_REF] Stone | Characterisation of the genomes of four putative vesiculoviruses: tench rhabdovirus, grass carp rhabdo -virus, perch rhabdovirus and eel rhabdovirus European X[END_REF]. The glyco protein (g) gene is commonly used for phylo -genetic studies, although the partial sequences of the RNA-dependent RNA polymerase (l) and nucleoprotein (n) genes have been used as well, producing clusters similar to those obtained with the g gene [START_REF] Ruane | Genetic diversity and associated pathology of rhabdovirus infections in farmed and wild perch Perca fluviatilis in Ireland[END_REF]. Based on the partial n gene and the complete g gene, various genogroups of PRV (A-D) have been defined [START_REF] Talbi | Genetic diversity of perch rhabdo -viruses isolates based on the nucleoprotein and glycoprotein genes[END_REF]. The phosphoprotein (p) gene has not been used to date for comparing PRV isolates, although it has been shown for EVEX that it may vary more than g and n, and therefore be more informative to compare isolates [START_REF] Bellec | Evolutionary dynamics and genetic diversity from three genes of Anguillid rhabdovirus[END_REF].

Most percid perhabdoviruses reported to date originate from wild animals introduced into experimental facilities and farms [START_REF] Dorson | A rhabdovirus pathogenic for perch, Perca fluviatilis L.: isolation and preliminary study[END_REF][START_REF] Dannevig | The first isolation of a rhabdovirus from perch (Perca fluviatilis) in Norway[END_REF][START_REF] Ruane | Genetic diversity and associated pathology of rhabdovirus infections in farmed and wild perch Perca fluviatilis in Ireland[END_REF].

However, the interregional trade of contaminated fish either for farming or for studying their biology may play an increasing role in the spread of viruses, either horizontally or vertically. When performed correctly, the disinfection of eggs may prevent transmission, suggesting that the virus does not penetrate the eggs and that transmission is pseudo-vertical. Pike-perch is a fish species increasingly farmed in Europe [START_REF] Dalsgaard | Farming different species in RAS in Nordic countries: current status and future perspectives[END_REF][START_REF] Kestemont | Biology and culture of percid fishes: principles and practices[END_REF] and is also sensitive to PRV as shown by an episode of high mortality caused by a virus in 1990 in France [START_REF] Nougayrède | Isolation of a rhabdovirus from the pike-perch Stizo stedion lucioperca (L.1358)[END_REF]. Since this episode, no mortality of this fish species has been published, although viruses have occasionally been isolated by the European Union Reference Laboratory for Fish Diseases (N. J. Olesen unpubl.). Here, we report a series of 5 outbreaks associated with variants of PRV during the same period at 2 distant sites. Based on our molecular data and other epidemiological information, we offer hypotheses on the origin of the virus involved in each outbreak.

Material and Methods __________________________________________________________

From a total of 5 distinct mortality episodes (M1-5) in 2016, pike-perch (zander) larvae were collected from 2 sites in 2 European countries to elucidate the etiology (Fig. 1). One site, a farm in Belgium, was affected by 3 successive episodes of mortalities (M1-M3) within a few months, each episode affecting at least 99% of the population. The larvae were kept in a recirculating water system at 17°C with appropriate levels of O2, NH4 and NO2. The second site, an experimental facility in France, experienced 2 episodes (M4-5) almost simultaneously on 2 batches of fry freshly imported from the Czech Republic and Hungary (240 000 and 200 000 fry, respectively). Both batches were distributed into 4 tanks each, with common recirculating water maintained at 21.5°C.

Histology

In the Belgian farm, the first batch of larvae affected by mortality was analyzed by histology. Larvae were fixed in 10% formalin and embedded in paraffin. Sections of 4-5 µm thick were stained with hema-toxylin-eosin-saffr on.

Cell culture

Larvae from 3 batches affected by massive mortalities (M1-3) in Belgium were processed in the CER laboratory for virus isolation (samples 16/65, 16/121 and 16/122 on 31 March, 27 May and 9 June, respectively). For these samples, hundreds of dead, moribund or alive larvae were euthanized (overdose of benzocaine) and immediately collected by filtration, divided in 3 batches and ground in mortar and pestle with sterile sand. The ground larvae were suspended in 10% antibiotic culture medium (v/v, penicillin at 5000 units ml-1 and streptomycin at 5000 µg ml-1) and centrifuged at 4000 rpm (3750 × g) during at least 15 min. Three cell lines were inoculated with the supernatant of the processed tissue samples, pure and diluted at 10-1, 10-2 and 10-3, with 2 wells of a 24-well plate per dilution: epithelioma papulosum cyprini (EPC), blue gill fry (BF-2) and fathead minnow (FHM;Gravell & Malsberger 1965). The 3 cell lines were grown in BHK21 medium (Gibco 21710) supplemented with 10% fetal bovine serum, 5% antibiotics (v/v of penicillin and streptomycin), gluta-max and tryptose phosphate broth. After inoculation, the 3 cell line plates were incubated at 14 and 21°C in 5% CO2 incubators.

Two batches of dead larvae from France were assigned the references 16/179 (origin of production, Czech Republic) and 16/183 (origin Hungary). They were processed in the LDA39 laboratory after a 1 d transportation at 4°C. For these 2 batches, weights of 1.5 and 0.57 g of 13 d old larvae were ground in MEM BHK21 medium (1/10, w/v) and inoculated in duplicates on EPC cells at 20°C and rainbow trout gonad (RTG-2) cells at 14°C at 2 dilutions (10-1 and 10-2) in 24-well plates. All plates were regularly inspected under a microscope for cytopathic effects (CPE); if no CPE were noted upon the first observation at 1 wk, a second passage was carried out. For the Belgian samples, aliquots of supernatants from cell cultures deve loping strong CPE were tested for the presence of various fish viruses, namely viral hemorrhagic septi cemia virus (VHSV), infectious hematopoietic ne cro sis virus (IHNV), spring viremia carp virus (SVCV) and infectious pancreatic necrosis virus (IPNV) using commercial ELISA kits (BioX) according to the manufacturer's instructions.

PCR

Total nucleic acids were isolated either from 200 µl of cell culture supernatant or 200 µl of larvae ground in phosphatebuffered saline (PBS) buffer (10% w/v) using a Nucleospin virus kit (Macher ey-Nagel) according to the provided protocol, except that the incubation with Proteinase K was 15 min at 70°C rather than 3 min at room temperature. Elution was performed in 50 µl of RNase-free water. For the 3 genes g, p and n, the Superscript III kit (Invitrogen) was used starting from 2-10 µl or 500 ng of total RNA extracted from cell culture or ground larvae, respectively. The amplification of the complete g gene was performed by targeting 2 overlapping fragments as already described, except that the reverse transcription and PCR were performed in a single reaction using the Superscript III kit [START_REF] Talbi | Genetic diversity of perch rhabdo -viruses isolates based on the nucleoprotein and glycoprotein genes[END_REF]. For amplifying the complete n gene, primers oPVP436 and oPVP437 (600 nM each) were designed from PRV sequences, upstream and downstream from the gene (Fig. 2). The RT-PCR started with a step at 48°C for 30 min, followed by a step at 94°C for 2 min and 35 cycles of 94°C for 30 s, 48°C for 30 s and 68°C for 80 s. For the complete p gene, primers pPVP438 and oPVP439 (800 nM each) were designed based on the complete PRV sequence. The RT-PCR started with a step at 48°C for 30 min, followed by a step at 94°C for 2 min, and 40 cycles of 94°C for 30 s, 48°C for 30 s and 68°C for 60 s. For viral amplification starting from total RNA from whole larvae, specific primers oPVP453 and oPVP454 were visually designed from the newly obtained n sequences from the viruses isolated in Belgium. They match perfectly with known PRV isolates belonging to the genogroups A, B and C previously described [START_REF] Talbi | Genetic diversity of perch rhabdo -viruses isolates based on the nucleoprotein and glycoprotein genes[END_REF]. However, they have a number of mismatches (4 and 5) with isolate 4925 from the genogroup D. Moreover, these 2 primers have respective ly 8 and 4-5 mismatches with 2 members of another Per habdovirus species, sea trout rhabdovirus (STRV) (GenBank AF434992) and LTRV (GenBank AF434991). Both primers were used at 400 nM; 500 ng of total RNA were added to the reaction. The RT-PCR started with a step of 58°C for 30 min, followed by a step at 94°C for 2 min and 40 cycles of 94°C for 30 s, 58°C for 30 s and 68°C for 30 s. All RT-PCR reactions ended with a 7 min elongation step. For sequencing, all PCR products were cloned in a TA vector (PCR4 TOPO, Invitrogen), and 3 clones were sequenced using universal M13 R and F primers and the Sanger method with a 3130 Gene -tic Analyzer (Applied Biosystems). In addition to the universal oligonucleotides, specific internal primers were used for sequencing long fragments of the n and g genes (Fig. 2).

All obtained sequences were assembled and edited using VNTI11.5 (Thermofisher Scientific). For cloned PCR products, a consensus sequence of 3 clones was created (without the primer sequences) and used for phylogenetic analysis. New sequences were deposi -ted in GenBank and compared with others already available (Table 1). The alignments and the phylogenetic analyses were performed using ClustalW and the maximum likelihood method (1000 bootstraps) implemented in MEGA7.0 [START_REF] Kumar | MEGA3: Molecular Evolutionary Genetics Analysis Version 3.0 for bigger datasets[END_REF].

Results ______________________________________________________________________

History of the outbreaks

In 2016, a total of 5 batches pike-perch larvae of various origins experienced massive mortality events in 2 Western European countries (Fig. 1): Belgium and France. The first batch of eggs was produced in February 2016 in a farm in Belgium. Because this farm used genitors from 7 different origins (wild and farmed pike-perch from 3 European countries) for egg production, it was not possible to identify the exact origin of the affected larvae. One day after hatching, the batch of larvae exhibited the first mortalities and virtually all larvae died. The tanks were disinfected and a second batch originating from the Czech Republic was introduced in May. It also succumbed massively at 10-11 d post hatching. A third batch from a different origin (Finland) was then introduced in June, but it was also affected by massive mortality at 12-14 d post hatching. In the same period of 2016, in France, 2 batches of larvae imported from the Czech Republic and Hungary were introduced into 2 different tanks in an experimental facility. Three days after feeding with Ar temia nauplü, the batch originating from the Czech Republic was affected by mortality, reaching 100% after 24 h. Four days later, the second batch (Hungary) exhibited a similar severe mortality event, which reached almost 100% after 1 d. No macroscopic lesions or parasites were observed on/in the moribund larvae, using a stereomicroscope and light microscope.

Histology

Histological observations were performed on a few larvae from the first outbreak (M1). One animal presented scattered lesions in the liver, kidney and oral mucosa (Fig. 3). In the liver, they consisted of small necrotic foci. Similar foci were also observed in the malpighian epithelia in the mouth. These (hydropic-type) lesions were associated with some vesiculation of the epithelium. In the kidney, the lesions were limited to the hematopoietic tissue. They were characterized by isolated or small foci of grouped necrotic cells. The brain, eyes and heart, when observed, remained free of any abnormalities.

Cell culture

Dead larvae from the 5 mortality episodes were assayed in cell culture in distinct laboratories. After incubation for 4-5 d, obvious CPE appeared for 3 samples (outbreaks M1, M2 and M3) tested at the CER laboratory in Belgium on 3 different cell lines (FHM, EPC and BF2) and at 14 and 21°C. The CPE were characterized by scattered foci of rounded and refringent cells (not shown). The foci became larger and centrifuge lysis ensued, leading to the total destruction of the cell layers after 3-4 d. These effects suggested the putative presence of a rhabdovirus according to CPE features. The 2 samples from epi -sodes M4 and M5, tested at LDA39 in France, did not produce any CPE after 3 passages of 7 d on EPC cells at 20°C and on RTG cells at 14°C and were therefore initially diagnosed as negative.

PCR detection and virus identification

The 3 CPE-positive cell culture supernatants were tested with a series of PCR targeting 2 portions of the g as well as the complete n and p genes of PRV, a common percid pathogen. All PCRs were positive and gave products at the expected sizes demonstrating the presence of viruses related to PRV in the 3 batches of larvae from Belgium (not shown). The sequences of the full length g, p and n genes were obtained for these 3 isolates and were genetically highly related to the type species PRV (GenBank no. JX679246), with similarities of 95, 94 and 92-93% (nucleic acids) for the g, n and p genes, respectively, between each sample and PRV. However, the highest identity levels (98-99 %) were observed for the g gene of a variant of PRV isolated from pike-perch from France in 1990 (reference 4890). The phylogenetic trees for n, p and g of the 3 viruses were consistent and grouped them in the genogroup A which includes the type species PRV (see Fig. 5) [START_REF] Talbi | Genetic diversity of perch rhabdo -viruses isolates based on the nucleoprotein and glycoprotein genes[END_REF].

Surprisingly, the virus identified in the first outbreak M1 was slightly different (98% identity for g, n and p) from the viruses from the 2 subsequent outbreaks at the same site (M2 and M3), these last two being identical (p) or nearly identical one to another (only 2 substitutions each for g and n). Considering that the 2 substitutions between the sequences of g and n of M2 and M3 may have originated from the quasi-species nature of the sample or errors during the PCR, despite the use of an error-proof Taq polymerase, viruses from M2 and M3 were likely the same. There were 9 (or 10) amino acid changes between the predicted G proteins of the M1 virus and the M2 (or M3). These results strongly suggested that the first outbreak had a different viral origin from the other two, while the second and third outbreaks were associated with a unique genotype.

Despite the negative results obtained in cell culture, samples 16/179 and 16/183 from the 2 mortality episodes in France (M4 and M5) were analyzed by RT-PCR in search of viruses similar to those previously found. The generic primers used for RT-PCR (highly degenerated and low melting temperature [Tm]) work well with concentrated viruses produced in cell culture, but are not adapted to viral RNA diluted in total nucleic acids from tissues. Thus, we designed new sets of primers (avoiding degeneracy and having high Tm), specific to the n gene for a range of genotypes related to those recently found. Using these primers, both samples from France appeared unambiguously positive, producing a unique band at the expected size (Fig. 4). As a positive control, an identical PCR product was obtained when testing isolate 16/121 from Belgium. The identities of the PCR products were confirmed by sequencing directly with the amplifying primers. Both PCR products had exactly the same sequences over 444 bp. Moreover, they were also strictly identical with the sequences obtained from isolates 16/121 and 16/122 (M2 and M3). There was therefore a strong evidence for the spread of the same virus between M2, M3, M4 and M5. This strong genetic link was further confirmed by the amplification and sequencing of the full-length p genes of the viruses identified in M2, M3, M4 and M5, which were strictly identical (Fig. 5).

Discussion

In spring and summer 2016, 5 mortality episodes affecting pike-perch larvae occurred in 2 very distant sites without any obvious relationship. Semi-thin sections of larvae from the first outbreak did not reveal the presence of an observable pathogen, but showed lesions that were compatible with a viral infection. For instance, multifocal necrosis was observed in the kidney and the liver, as already described in tissues infected by perch perhabdoviruses [START_REF] Henshilwood | The emergence of rhabdovirus infections in farmed perch Perca fluviatilis in Ireland[END_REF][START_REF] Gadd | Characterization of perch rhabdovirus (PRV) in farmed grayling Thymallus thymallus[END_REF]). To our knowledge, the oral lesions observed in our study have never been reported before in PRV infections. More reports of lesions observed in this organ are needed to evaluate the pathognomonic potential. Conversely, no lesions were observed in the brain despite the likely presence of the virus in this tissue and previous reports of congestion in the meninges [START_REF] Dorson | A rhabdovirus pathogenic for perch, Perca fluviatilis L.: isolation and preliminary study[END_REF], Hen-shilwood et al. 2009). Unfortunately, we did not ex -amine the pancreas despite the frequent lesions reported in other cases. Until the best target organ for detecting PRV is identified, either by histopathology or PCR, it is recommended to sample various organs in any future putative cases.

For each outbreak, rhabdoviruses related to PRV were found either by cell culture and PCR (M1, M2 and M3), or only by PCR with new assays developed here (M4 and M5). To our knowledge, this is the first report of the presence of PRV in Belgium. For outbreaks M4 and M5, the virus could not be cultured for unknown reasons, possibly due to poor conservation of the samples or a toxic effect. However, PRV was unambiguously detected by PCR in these 2 samples. Finally, 2 related, yet distinct, variants of PRV were found among the 5 episodes. Despite the apparent absence of connections between the 2 sites, the complete and partial sequences of key viral genes and other epidemiological data suggest the involvement of 2 viral genotypes in the various outbreaks. The first episode M1 occurred in larvae originating from 7 batches of genitors from farmed and wild fish from 3 European countries. Therefore, 1 genotype was likely transmitted to the larvae from 1 or several of these genitors. After culling, the farmer thoroughly disinfected the tanks, a procedure that probably eradicated the first virus. The following outbreak M2 affected larvae from the Czech Republic, and the third outbreak affected larvae originating from Finland. Between outbreaks M2 and M3, the facilities were not disinfected. Therefore, for the site in Belgium, a likely scenario consistent with the molecular data is an initial contamination of the first batch of larvae by a virus carried by genitors of different origins, followed by its eradication during the disinfection performed just after the outbreak. After this first episode, a second distinct virus was likely introduced with the second batch of larvae from the Czech Republic, affecting this batch and also contaminating the third batch originating from Finland, due to the absence of disinfection between batches. Under this scenario, disinfection efficiently inactivated the first virus and prevented the infection of the subsequent batch. Other scenarios are possible, such as the introduction of 2 or more viruses with the first batch, and the subsequent isolation of only 1 virus during each episode. This hypothesis is plausible considering the limited sampling of the fish combined with a putative selective effect of cell culture and a limited sequencing of the clones obtained from the PCR products. With the new PCR tools described here, it will be possible in the future to amplify and sequence viral sequences directly from different batches of larvae without using cell culture and PCR cloning.

Regarding episodes M4 and M5 successively affecting 2 batches of different origins at the same site, the same virus was found as determined by the perfect identity between the compared full-length p sequences. Therefore, the same virus was likely transmitted between the 2 batches, probably via the water system. Surprisingly, this virus was also identical to those of episodes M2 and M3, despite the absence of any direct epidemiological connection. Upon inquiry, it was found that the batches from M2 and M4 had exactly the same origin, from a site in the Czech Republic, epidemiologically linking the farm in Belgium and the experimental site in France. This link explained both the identities between M2 and M4 viruses as well as between M2/M3 and M4/M5 through horizontal transmission.

The likely scenario of contamination of the present outbreaks implicated that both horizontal and pseudo-vertical transmission modes were active in spreading the viruses between countries and batches of fish. The control of the disease at the continental scale will therefore require the use of a large panel of methods to limit both modes of dissemination. Regarding vertical transmission, thorough disinfection of pike-perch eggs can prevent the infection of fry, although protocols of disinfection still need to be standardized and optimized, i.e. to avoid toxic effects [START_REF] Rodger | Diseases and health management in perch farming[END_REF][START_REF] Lahnsteiner | Investigations on the effect of formalin and iodophor on embryo and larvae development in pikeperch, Sander lucioperca[END_REF]. Regarding horizontal transmission, the proposed scenario of infection for the second Belgian batch highlights that disinfection of the tanks and the water circulation system is efficient and can prevent the transmission of the virus from a first batch to a second. Diagnostic tools and gene sequencing were useful in the present cases, both to detect the presence of PRV and to formulate hypotheses of spread.

Although cell culture allowed the diagnosis of the 3 outbreaks in Belgium, it was not efficient for isolating the virus in France, and it did not lead to PRV detection. Conversely, PCR led to rapid diagnosis and, combined with sequencing and phylogenetic analysis, allowed an accurate comparison of the sequences between outbreaks and with those already in databases. Among the new PCR protocols proposed in our work, the one amplifying a portion of the n gene is the first, to our knowledge, that can be widely used for detecting a range of PRV variants directly from tissue. The range of variants potentially detected encompasses the genogroups A, B and C previously described [START_REF] Talbi | Genetic diversity of perch rhabdo -viruses isolates based on the nucleoprotein and glycoprotein genes[END_REF]. This method should be extensively validated and transferred to European laboratories receiving samples of percids for diagnosis. Other more rapid and specific methods, such as Taqman-based realtime PCR, should be developed as well. More globally, the control of perhabdo -viruses dispersal in European percid farms requires the generation of genetic data and the development of PCR-based methods specific of viral species (LTRV, PRV, etc.).The high similarities between the 2 distinct viruses presently identified and the pike-perch virus isolated in France in 1990 are puzzling since there is no known link between outbreaks that occurred 26 years apart. The simplest explanation is that the virus from 1990 has the same geographic origin as those from 2016, namely the Czech Republic. We could not find information on the origin of the fish in 1990, but transfers of pike-perch have been frequent these last years from the Czech Republic to France. Therefore, we can only speculate on such a transfer of contaminated fish, which implies that the virus from 1990 is an ancestor of the 2 recent ones and has slightly diverged into variants occasionally dispersed over almost 3 decades. Another hypothesis involves an unknown source of virus which spread in various European countries before 1990. More generally, this high genetic similarity underlies the existence of a viral population which has been widely spread across Europe, most probably by trade of pike-perch or an alternative reservoir, possibly perch. Further accurate identification of perhabdoviruses from percids should be a priority to continuously improve probe-based diagnostic tools and trace the movements of viruses. This effort, combined with disinfection of eggs and the facilities, should help to reduce the present and future burdens of the disease on this fish species, and perch, which are both increasingly farmed. However, although some European farms have already successfully developed some control measures, many others still ignore the risks associated with this group of perhabdoviruses or fully depend on the introduction of fry, genitors or juveniles from sources that are not certified virus-free. Methods that can diagnose healthy carriers with very low viral loads or sick animals carrying un known genotypes are needed to select and maintain virus-free genitors and protect inter-regional exchanges of farmed juveniles.

Table 1 .Figure 4 .Figure 5 .

 145 Figure 1. Features of 5 mortality episodes (M1-5) affecting pike-perch larvae at 2 distant sites in 2016. M1, M2 and M3 occurred on a farm in Belgium; M4 and M5 at an experimental facility in France. M4 and M5 affected larvae of distinct geographic origins that were distributed in 8 tanks (4 and 4) at the French site. For simplification, only 1 tank is represented for each episode

Acknowledgements ____________________________________________________________

We thank an anonymous farmer who provided invaluable data on the mortality episodes. This work is dedicated to the late Georges Plassiart.


Jean-Philippe Farrugia
email: jean-philippe.farrugia@univ-lyon1.fr

Luc Billaud

Guillaume Lavoué
email: guillaume.lavoue@enise.ec-lyon.fr

Adaptive streaming of 3D content for web

Keywords: Computing methodologies → Virtual reality Virtual Reality, Streaming, Mesh compression, DASH protocol

INTRODUCTION

3D content is now more and more common, as technologies and techniques are developed to widespread its usage. Computer-Aided Design softwares, video games, industrial or scientific applications now all propose 3D content to their users. Hardwares like GPUs (Graphic Processing Units) allow, in conjunction with algorithms like shaders, computers to efficiently display this 3D content. Since a few years now, the rising 3D technology is Virtual Reality (VR). By immersing the users (using head-mounted displays) in a virtual 3D environment, VR proposes a seemingly realistic experience. Moreover, with the introduction of autonomous head-mounted displays, like the Oculus Quest, we got rid of constraints like a cable and a PC, as well as a restricted playground. However, this comes at the cost of performance and thus introduces new constraints on the size and complexity of the 3D world that can be displayed.

These new constraints are amplified by the fact that, in most applications, the 3D content is always more and more complex and detailed. Another novelty is that standards such as WebGL and WebXR [START_REF]WebXR Device API[END_REF] now enables full 3D VR experience through web browsers. In those 6 DoFs (degrees of freedom) web-based VR applications, the 3D content has to be streamed from a remote web server; this may induce drops in performance and latency due to transmission, which may be both very detrimental for the user experience. In this context, several authors (e.g., [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF][START_REF] Park | Rate-Utility Optimized Streaming of Volumetric Media for Augmented Reality[END_REF][START_REF] Van Der Hooft | Towards 6DoF HTTP Adaptive Streaming Through Point Cloud Compression[END_REF]) proposed utility metrics and selection strategies to prioritize which 3D objects to fetch from the server according to the user viewport position and movement, in order to optimize at run-time the quality of what is being visualized. Those proposed algorithms use each different features (e.g., tiling, compression, levels of details), different utility metrics and different streaming strategies; it is thus difficult to compare them and evaluate the best choices in this large parameter space. In this work, we address this problem by providing an open-source framework, which we use for the evaluation and comparison of those different features, metrics and strategies. Our contributions are the following:

• We propose and release publicly, in open source, a DASH-based web virtual reality application integrating several features, metrics and streaming strategies from the state of the art. The source code is publicly available on our GitHub repository 1 . • We provide an exhaustive evaluation and comparison of 30 combinations of metrics and strategies, under 3 different bandwidths and for 3 camera paths for a museum scene containing more than 880MB of 3D content. We explored a large set of parameters, leading to the generation of a total of 720 captured videos corresponding to user simulated navigation paths. • We isolate and evaluate the effect of three features highly relevant for 3D streaming : 3D mesh compression, levels of details and visual quality index integration.

The remainder of this paper is organized as follows : section 2 review the related work about adaptive 3D content streaming. Section 3 describes our implemented system, while section 4 details the experimental results. Finally, in section 5, we provide conclusions and perspectives.

RELATED WORK

This related work section focuses on web-based adaptive streaming of 3D content, an more particularity on the algorithms introduced to optimize and prioritize the downloads in order to optimize the quality of experience. The reader can refer to [START_REF] Maglo | 3D mesh compression: Survey, comparisons, and emerging trends[END_REF] for a complete survey about 3D mesh compression.

With the introduction of WebGL 10 years ago, several algorithms were introduced for 3D content compression and streaming over the web [START_REF]Draco[END_REF][START_REF] Lavoué | Streaming Compressed 3D Data on the Web using JavaScript and WebGL[END_REF][START_REF] Limper | SRC -a streamable format for generalized web-based 3D data transmission[END_REF][START_REF] Ponchio | Multiresolution and fast decompression for optimal web-based rendering[END_REF]. They are based on different compression strategies, compliant with a fast web decoding. Those algorithms focus on optimizing the compression rate and the streaming of one single 3D object, without any consideration on how to optimize the delivery of a whole scene composed of several objects. However, they constitute relevant tools for our problematic; the DRACO codec [START_REF]Draco[END_REF] 1 https://github.com/Plateforme-VR-ENISE/AdaptiveStreaming from Google is integrated into our implemented framework.

Pioneering works related to our focus of interest were introduced only three years ago, concurrently by Forgione et al. [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF], van der Hooft et al. [START_REF] Van Der Hooft | Towards 6DoF HTTP Adaptive Streaming Through Point Cloud Compression[END_REF] and Park et al. [START_REF] Park | Rate-Utility Optimized Streaming of Volumetric Media for Augmented Reality[END_REF]. Those three works proposed systems and algorithms for adaptive streaming of scenes comprising multiple 3D models (either 3D point clouds or meshes). In particular, they proposed utility metrics and strategies to schedule and optimize the delivery of the 3D models (or their levels of details -LoDs) according to the network and the viewport of the user. Further methods and systems were introduced latter, based on the same or close principles [START_REF] Lievens | Adaptive Web-Based VR Streaming of Multi-LoD 3D Scenes via Author-Provided Relevance Scores[END_REF][START_REF] Slocum | VIA: Visibility-aware Webbased Virtual Reality[END_REF][START_REF] Subramanyam | User Centered Adaptive Streaming of Dynamic Point Clouds with Low Complexity Tiling[END_REF]. Most of the above works intent to remain compatible with the Dynamic Adaptive Streaming over HTTP (DASH) standard, which is already widely deployed for streaming adaptive video content on the Web. These frameworks focus on 3D content represented by textured meshes [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF][START_REF] Lievens | Adaptive Web-Based VR Streaming of Multi-LoD 3D Scenes via Author-Provided Relevance Scores[END_REF][START_REF] Slocum | VIA: Visibility-aware Webbased Virtual Reality[END_REF] or colored point clouds [START_REF] Park | Rate-Utility Optimized Streaming of Volumetric Media for Augmented Reality[END_REF][START_REF] Subramanyam | User Centered Adaptive Streaming of Dynamic Point Clouds with Low Complexity Tiling[END_REF][START_REF] Van Der Hooft | Towards 6DoF HTTP Adaptive Streaming Through Point Cloud Compression[END_REF]. They consider different tools, such as compression, tiling [START_REF] Park | Rate-Utility Optimized Streaming of Volumetric Media for Augmented Reality[END_REF][START_REF] Subramanyam | User Centered Adaptive Streaming of Dynamic Point Clouds with Low Complexity Tiling[END_REF], texture LoD [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF], quality index [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF], 3D object grouping [START_REF] Slocum | VIA: Visibility-aware Webbased Virtual Reality[END_REF] or manual prioritization [START_REF] Lievens | Adaptive Web-Based VR Streaming of Multi-LoD 3D Scenes via Author-Provided Relevance Scores[END_REF].

Since these algorithms use heterogeneous data, tools and strategies then it becomes very difficult to have a clear idea of the best choices. In this work, we propose an open-source DASH compliant web-based virtual reality framework that integrates and combines a large set of tools, metrics and strategies.

OUR ADAPTIVE STREAMING FRAMEWORK 3.1 General description and data preparation

Our implemented framework is inspired by [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF] and is compliant with DASH. It implements a scenario of an interactive visit to a virtual museum composed of high quality 3D models. On the server side, the 3D models composing the scene are simplified into 10 levels of details. Each level of details (LoD) is compressed with Google Draco and the resulting .drc files are stored. Each LoD is also associated with a quality score computed using the HDR-VDP2 perceptual quality metric [START_REF] Mantiuk | HDR-VDP-2 : A calibrated visual metric for visibility and quality predictions in all luminance conditions[END_REF]. This metric intends to predict the visual fidelity of the LoD with respect to the pristine unsimplified object. Note that HDR-VDP2 is an image-based metric; we computed its value for each 3D model by applying it to the most perceptually-relevant screenshot. On the client side, a script is charged to evaluate the current state of the scene, the user's position, rotation and trajectory and the client's bandwidth to determine the best objects and their levels of detail to download. Once this is determined, the corresponding files are requested, decompressed and then displayed, and the process can start again, until all the objects have their best level of detail imported.

To determine which levels of detail are the best and have to be imported, different combinations of strategies and metrics were implemented, taken from [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF][START_REF] Van Der Hooft | Towards 6DoF HTTP Adaptive Streaming Through Point Cloud Compression[END_REF] ; they are presented below.

Utility metrics from [2, 15]

Those metrics 𝑈 (𝑚) reflect how much an object 𝑚 is useful to the global quality of the scene. Intuitively, the closer and the bigger an object is, the more useful it is. The implemented metrics are the following :

• Distance : Distance between the object and the camera.

𝑈 𝐷 (𝑚) = 1/𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒 (𝑐𝑎𝑚𝑒𝑟𝑎, 𝑚) 2

Strategies from Forgione et al. [2]

These strategies serve to select one level of detail 𝑚 𝑙 of a given object 𝑚 to be imported. This 𝑚 𝑙 is the one considered as the best, i.e., the one with the best score as computed by the utility metrics presented above. Each strategy has a different criterion, and a different way to calculate the score according to the metrics above.

Note at, at each selection step, candidate LoDs are those which are in the current view frustum and in a predicted view frustum computed using a linear predictor of the position and the rotation of the camera. The temporal horizon for this viewpoint prediction is set by default to 2 seconds in our system. The impact of this value is evaluated in the experiments.

• Naive1 : The score is the utility of the object multiplied by the quality index of the level of detail. This strategy is most likely to select an object that is currently visible. • Greedy1 : The score is the variation of utility of an object between the moment it is imported and the temporal horizon, multiplied by the quality index of the level of detail. This strategy is most likely to select an object that will be visible after some time. • Optimize1 : (called Proposed in the original article) The score is the integral of the utility of an object between the moment it is imported and the temporal horizon, multiplied by the quality index of the level of detail. We do it by calculating a Riemann sum. This strategy is most likely to select an object that is visible over the full period.

Strategies from Van der Hooft et al.[15]

These strategies select and import multiple levels of detail at a time.

Here, we are filling a buffer, which corresponds to a number of bits that can be imported (downloaded and decompressed) in a certain amount of time (by default 2 seconds × the bandwidth). A loop will go through all the levels of details of all the objects and allocate bits to these LoDs until the buffer is full. The strategies loop through the levels of details differently, thus allocating the bits differently.

• Greedy2 : We loop through all of the levels of detail of an object before considering the next object. Objects are considered by decreasing utility. • Uniform2 : We loop through a certain level of detail (e.g. level 1) for all the objects in decreasing utility order before considering the next level of detail (e.g. level 2). As for the temporal horizon above, the impact of the buffer size (set to 2 seconds * bandwidth) is evaluated in the experiments.

Implementation

In the context of streaming use, it seemed natural to use a webbased framework for our implementation. We selected Babylon.js, which has the advantage of being WebXR compatible and allowing the use of javascript WebWorkers. WebWorkers were used to be able to run the decompression of the levels of details in parallel to the user visualization and interaction (thus preventing any freeze). Typescript, a superset of javascript, is used to allow more rigorous object programming. The architecture of our application is shown in Figure 2. It includes two singletons, an instantiated class, and service classes.

Singletons.

• The Museum Class creates the context of the application and handles its basic operations: inputs handling, scene display, asset import.

• The ObjectManager Class is the application scheduler. It manages the initialization, positioning and display of all museum objects in the scene as well as the execution of strategies.

Instantiated class.

• The MuseumObject class represents an object in the museum and is multi-instanced by the ObjectManager for each object in the scene. This class contains all the metadata (name, area, size, visual quality index) and the levels of detail generated for this object. All level of details are stored as independent .drc meshes, compressed with the Draco Framework. The MuseumObject class uses methods of the DracoCompression class, provided by BabylonJS, to decompress level of details asynchronously.

In our implementation, a single pool of 5 DracoCompression web-workers is used for the whole scene.

Services.

• The SpeedManager static class gathers speed and bandwidth calculation functions.

• The Metrics class includes metric calculation functions • The Strategies class brings together the strategy calculation functions

The overall behaviour of the application is as follows: an instance of the application is created with the Museum class. It then creates an instance of the ObjectManager singleton, which itself will dynamically create the scene's objects with the MuseumObject class. At runtime, ObjectManager applies metrics and strategies to determine the appropriate level of detail for each museum object. Each museum object instance calculates its speed and bandwidth data.

Differences with the state of the art

As stated above, our system integrates the metrics and strategies from both Forgione et al. [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF] and Van der Hooft et al. [START_REF] Van Der Hooft | Towards 6DoF HTTP Adaptive Streaming Through Point Cloud Compression[END_REF]. However some differences remain with regards to their frameworks : Van der Hooft et al. [START_REF] Van Der Hooft | Towards 6DoF HTTP Adaptive Streaming Through Point Cloud Compression[END_REF] considered colored point clouds whereas we consider textured meshes. Our system uses multiple geometrical levels of detail (i.e., different meshes) while Forgione et al. [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF] had only one geometrical level of detail per object but multiple texture resolutions. They use a quality index for the textures which is a simple PSNR. Our quality index (HDR-VDP2 [START_REF] Mantiuk | HDR-VDP-2 : A calibrated visual metric for visibility and quality predictions in all luminance conditions[END_REF]) was designed to reflect the perceived quality and demonstrated good correlation with subjective opinion on a dataset of distorted 3D models [START_REF] Nehmé | Visual Quality of 3D Meshes With Diffuse Colors in Virtual Reality: Subjective and Objective Evaluation[END_REF]. Another point is that Forgione et al. [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF] did not use a compression algorithm. Finally, we obviously introduced differences in the algorithm implementation since research papers do not contain full implementation details.

EXPERIMENTS AND RESULTS

Experimental setup

To demonstrate the utility of the proposed software, we compare the different combinations of strategies and metrics presented above. We also assess the influence of the different parameters of our system. We took inspiration from Forgione et al.'s experimental process [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF]. We created a museum scene composed of 20 high quality 3D models between 20K and 635K vertices, for a total of 880MB of uncompressed data (including 5MB for the museum building itself). Those models were taken from the Creative Common collections of Sketchfab. We created three different predefined camera movements in the scene, corresponding to realistic exploration paths. Each of these animations is 21 seconds long. We also considered three network bandwidth conditions : 2 Mbps, 4 Mbps, and 30 Mbps and two values for the temporal horizon / buffer size: 1s and 2s. Figure 3 illustrates several views of our 3D environment. For each combination of conditions (3*animations, 6*strategies, 5*metrics, 3*bandwidths and 2*Temporal horizons/buffer size), the navigation was simulated using our adaptive streaming engine and recorded, giving us a total of 540 recordings. To objectively evaluate the quality of those resulting renderings, as in [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF], we compared them to reference recordings using PSNR. Those references were offline versions, where each object of the scene was initially loaded with its maximum quality, thus having the best possible quality in the video. To compute the PSNR between those test and reference recordings, they were sampled each 100ms giving a total of 210 frames to compare. A particular care was taken to be sure that the frames of each pair to compare have a perfect temporal correspondence. Additional recordings were computed for different parameter settings (visual quality index on/off, levels of detail on/off) giving a total of 720 recording, i.e. 151200 test images plus 630 references ones.

Results

In this section, we evaluate and compare the performance of the different combinations of strategies and utility metrics, with regards to the bandwidth, the camera path and to the temporal parameters. We also evaluate the impact of three features of our system : the perceptual quality metric, the compression algorithm and the use of levels of details.

Best metrics and strategies according to the bandwidth Figures 4 illustrate boxplots of PSNR values according to the metrics (top row) and according to the strategies (bottom row), for the three tested bandwidth values. For each metric (resp. strategy) each boxplot aggregates PSNR values of all frames for all the strategies (resp. metrics), and all camera paths. Note that those results are for standard conditions meaning that we activate the perceptual quality index, the compression and the levels of detail and the values of the temporal parameters are set to 2s. The performances of the different utility metrics are very close to each others with a similar trend regarding the effect of bandwidth. It is interesting to observe the strong improvement between 2Mbps and 4Mbps, whereas 30Mbps brings a relatively small additional quality. The best metrics are Surface and VisiblePotential. For the strategies, surprisingly, the simplest provide the best results : Naive1 and Greedy2. One explanation is that these strategies require less operations to execute than the others. This result is a bit surprising as they are presented as bad in their respective articles. This emphasizes the need of a common public implementation, since the real-time performance of such interactive systems can be impacted by tiny details of implementation that do not necessarily appear in the research papers. Another surprising result is the decrease in performance of the Uniform2 strategy when passing from 4Mbps to 30Mbps. By checking in details the results, we found that the explanation could be the time processing of the buffer filling algorithm (as described in Section 3.4). Indeed, since this algorithms loop through all objects until it fills the buffer, then a large buffer size could create latency in the downloading decisions.

Best metric/strategy combinations Figure 5 presents the performance of each combination of metric/strategy in term of PSNR averaged over all the frames and all the animations for each bandwidth (still for the standard conditions). Methods are ordered by their average performance (i.e., mean over the three bandwidths). For the sake of visibility we present only the 20 best combinations (among 30). Overall, the best combinations are the following: Naive1-Surface, Naive1-Visible, Naive1-Potential and Greedy2-VisiblePotential. Moreover, none of the best strategies from Forgione's and van der Hooft's articles [START_REF] Forgione | DASH for 3D Networked Virtual Environment[END_REF][START_REF] Van Der Hooft | Towards 6DoF HTTP Adaptive Streaming Through Point Cloud Compression[END_REF], respectively Opti-mize1 and Hybrid2, appear in our best combinations. As mentioned above, this may be probably explained by a different implementation of the algorithms and the strategies, a different test environment or even a slightly different measurement process. It is interesting to notice that the respective ranks of the combinations actually depend on the bandwidth conditions. Several methods are very stable (Naive-Surface), while others are significantly impacted by the decrease in bandwidth (e.g., greedy2-potential). It is noteworthy that for 30Mbps and 4Mbps the greedy2-potential method is actually the best one. to new objects entering the field of view. However, the spikes are not happening at the same time and not with the same amplitude, because the choices made by the combinations regarding the levels of detail to import are not the same.

Influence of the temporal horizon

The horizon and the buffer, which are parameters used by the different strategies were suspected to have a large influence on the performances of the algorithms. Van der Hooft et al. [START_REF] Van Der Hooft | Towards 6DoF HTTP Adaptive Streaming Through Point Cloud Compression[END_REF] have shown that the buffer have an impact on the number of freezes and the video quality. They showed that for higher buffer values, the prediction accuracy and then the video quality decreases, but the resilience to freezes increases. We performed our quality evaluation for two values of these parameters: 1s and 2s for the horizon and the buffer size. Statistical tests shows that the parameters have an impact on the performance, and that a buffer/horizon of 2 seconds is performing significantly better than a buffer/horizon of 1 second. Those results are confirmed by Figure 6.

Influence of the camera path The performance of the system is obviously dependent on the complexity of the camera path, its velocity and the 3D objects that are present. Figure 7 (left) illustrates this behavior. The camera path UpperRoom generates globally the worst results (this trend is general for all methods).

Influence of the visual quality index

Only three strategies use a quality index. Those strategies are Naive1, Greedy1 and Optimize1. Therefore, only these strategies are considered in the results below. In these strategies, the quality index is used to weight the utility of an object. Then, to evaluate our combinations without the use of the visual quality index, we simply replace it by 1. Figure 7 (center) clearly shows that the visual quality index (HDR-VDP2 [START_REF] Mantiuk | HDR-VDP-2 : A calibrated visual metric for visibility and quality predictions in all luminance conditions[END_REF]) brings a significant improvement of the PSNR (confirmed by statistical test).

Influence of the levels of detail Figure 7 (right) clearly shows that the levels of detail have a significant impact on the PSNR (confirmed by statistical test). This result was expected as simplified meshes are always closer to the reference than the background.

Influence of compression

Table 1 shows a comparison of the download time of some .obj files and the import time of their .drc counterparts (i.e., compressed by Draco [START_REF]Draco[END_REF]). In this table, the calculations are made with a high bandwidth (30 Mbps) and an average decompression speed of 8 Mbps (the average decompression speed in our setup). In those conditions, the compressed files require around 90% less time to be imported than the uncompressed ones. This data clearly indicates that compression with Google Draco is very advantageous and reduces the import time of meshes in almost every situation. Moreover, .obj files might be long to parse and most OBJ Loaders are not meant to be used during runtime and are not multi-threaded, while Babylon.js's DracoCompression object is.

CONCLUSION AND DISCUSSION

In this work, we present our open-source framework for streaming 3D graphics in 6DoFs scenarios. We used our framework to evaluate 6 strategies and 5 metrics from the state of the art in a virtual museum scenario. We determined the best combinations for several bandwidths and demonstrated the impact of several tools and parameter values. Those results constitute first steps toward the full understanding and development of optimized streaming systems for 6 DoFs virtual experiences. Our results and the differences we observed regarding state-of-the-art conclusions, emphasized the fact that streaming systems are difficult to compare since many details of implementation may influence the results. The release of our source code is an attempt to provide the community with a common basis for comparison. Beyond the considerations raised above, our implemented system owns several limitations that should be improved in future work. First, levels of details should be considered also for texture, and not only for meshes. For instance, the progressive algorithm from Caillaud et al. [START_REF] Caillaud | Progressive compression of arbitrary textured meshes[END_REF] proposes a bit-allocation framework which multiplexes mesh and texture levels of details to optimize the visual quality for a given bit budget. Another way of improvement concerns the visual quality index: we used an existing image-based metric calibrated for natural image distortions; however, very recently, several authors introduced metrics specifically suited for visual quality assessment of 3D graphics [START_REF] Nehmé | Visual Quality of 3D Meshes With Diffuse Colors in Virtual Reality: Subjective and Objective Evaluation[END_REF][START_REF] Nehmé | Textured Mesh Quality Assessment: Large-Scale Dataset and Deep Learning-based Quality metric[END_REF]. Finally, our performance metric is the per-frame PSNR ; this metric is obviously not directly related to the quality of experience which is our main interest. Note that we also computed SSIM values on top of PSNR ; however reported values were not significant since this perceptual metric is not suited for large scene renderings where only localized distortions occur. The only way to measure and evaluate the quality of experience would be to conduct subjective user tests. Such user studies would also be a mean to assess if the quality of user experience is correlated or not with our evaluation measure. We believe that our publicly-released platform may constitute an excellent basis for that, as well as for exploring further factors (e.g., including visual attention models, and so on).

•

  Surface : Surface of the object divided by its squared distance to the camera. 𝑈 𝑆 (𝑚) = 𝑠𝑢𝑟 𝑓 𝑎𝑐𝑒 (𝑚)/𝑑𝑖𝑠𝑡𝑎𝑛𝑐𝑒 (𝑐𝑎𝑚𝑒𝑟𝑎, 𝑚) 2 • Visible : Area on the screen taken by the bounding box (BB) of the object relative to the screen's area. 𝑈 𝑉 (𝑚) = 𝑠𝑐𝑟𝑒𝑒𝑛𝐴𝑟𝑒𝑎(𝐵𝐵(𝑚)) • Potential : Area on the screen of the object if the camera were oriented towards the center of this object. 𝑈 𝑃 (𝑚) = 𝑠𝑐𝑟𝑒𝑒𝑛𝐴𝑟𝑒𝑎 𝐶𝑎𝑚𝑒𝑟𝑎𝑇 𝑜𝑤𝑎𝑟𝑑 (𝑚) (𝐵𝐵(𝑚)) • VisiblePotential : It is equal to the Visible metric if the object is in the field of view, and is equal to Potential otherwise.

Figure 2 :

 2 Figure 2: Architecture of our application

Figure 3 :

 3 Figure 3: Several views of our virtual environment, taken from the MainRoom camera path (first row), the StatueRoom camera path (second row) and the UpperRoom camera path (third row).

Figure 4 :

 4 Figure 4: Boxplots of PSNR values according to the utility metrics (top) and strategies (bottom). Mean values are represented by the red dots.

Figure 1 Figure 5 :

 15 Figure 5: Performance per combination for each of the 3 bandwidths. The performance is computed as the PSNR averaged over all camera paths. Combinations are ordered by increasing average performance over the 3 bandwidths.

Figure 6 :

 6 Figure 6: Boxplots of PSNR values of the strategies, according to the buffer/horizon values.

Figure 7 :

 7 Figure 7: Boxplots of PSNR values according to the camera path (left), the use of quality metric (middle) and the use of levels of details (right).

Table 1 :

 1 Comparison of the import time for uncompressed and compressed meshes. Bandwidth = 30Mbps, decompression speed = 8 Mbps. Δ expresses the gain in the time provided by the compression.

	Name	Uncompressed (.obj) Compressed (.drc) Size (KB) Time (s) Size (KB) Time (s)	Δ
	Dinosaur	78185	20.85	794	1.01	95%
	Lion	45492	12.13	794	1.01	92%
	Lizard	4402	1.17	84	0.11	91%
	Orchid	2221	0.59	52	0.07	89%
	Shuttle	10583	2.82	250	0.32	89%

ACKNOWLEDGMENTS

This work was partly supported by French National Research Agency as part of ANR-PISCo project (ANR-17-CE33-0005), and by Computer Science Department of IUT Lyon 1, Bourg en Bresse, France.