The third year of VRTogether is in full swing, and despite the recent pandemic scare our consortium is hard at work creating the technology and content for our third-year pilot. As we have described before, pilot 3 will involve an interactive scenario where users take on an active role trying to solve the mysterious murder of Elena Armova. 

Pilot 1 involved a one-take interrogation scene observed by our users, and was created using three different content formats; 360 degree video, a 3D scene with billboard video, and a 3D scene with 3D characters. For this last option the actors were captured using a custom photogrammetry rig from Artanim with more than 90 cameras, after which their 3D mesh was reconstructed and subsequently rigged and animated using mocap data. The three formats allowed us to evaluate their tradeoffs in a VR context. The results indicated that in general the video billboards were preferred by users for their visual quality and natural appearance, but their main shortcoming is that user movement is very limited before such billboards no longer maintain their illusion.

Pilot 3 puts the users at the scene of the crime. Standing at and moving between different locations in Elena Armova’s apartment, they observe and interact with the characters in the scene. This, given the aforementioned shortcomings of a video billboard solution, means we will see the return of 3D characters. An additional downside of a billboard solution would have been the difficulty to have a seamless continuity of a variety of recordings. The interactivity inherent to the plot will see our characters respond to our user’s actions, wait for their response and progress along several possible paths. To seamlessly blend these various branches in our timeline, the only truly feasible option is to opt for 3D characters, driven by a full performance capture (motion capture for the full body including the fingers and face). 

Having evaluated the 3D characters of Pilot 1, the consortium wanted to aim for a higher visual quality for Pilot 3. While a commercial 3D photogrammetry solution has been considered, both financial and scheduling constraints made this impractical. Luckily content creation solutions have not stopped evolving over the last few years, among which Reallusion’s Character Creator ecosystem – as well as other tools – which will be used to create our 3D characters. Characters created with the tools in this ecosystem are easily animated in real-time 3D engines such as Unity, by motion capture data from the body and hands all the way to facial animation. 

Besides executing the motion capture, Artanim and its artists have taken on the task of creating our high quality virtual characters. The first step in the process is the collection of as much reference material as possible. The COVID-19 pandemic made taking in-studio headshots impossible, but some of the actors involved were already photographed as a part of pilot 1, while others supplied as much reference material as they possibly could. This includes high quality photos of their head from all angles, full body shots, as well as a set of body measurements to make sure their virtual counterparts match their own morphology. Ensuring a close match between the two also simplifies the retargeting stage while post-processing the motion capture.

Modern AI approaches have evolved quite significantly in recent years, leading to major advances in image processing in general, and obtaining 3D information from monocular views in particular. These developments find their way into content creation tools such as Character Creator’s Headshot AI plugin used as a basis for our character’s heads. Such tools do a commendable job based on a single image from a single view, but the creation of a more correct likeness still involves quite a lot of manual work, taking the generated output as a basis, carefully modifying the obtained 3D mesh to more closely match our actors’ morphologies. 

This is then followed by the addition of hair geometry, textures, shaders and materials to get a final real-time VR ready result.

Without the use of 3D scans, the creation of the body is still a largely artistic process. Starting from a basic avatar body, it is up to the artist to adjust the basis to the actor’s appropriate sizes, and to adapt or model 3D clothing and accessories – including meshes, textures and materials – to get a high quality end result. 

The end result is a high quality 3D representation of our actors, which can be used in interactive real-time VR scenarios for an exciting immersive experience. 

Year 3 of VRTogether has started, which is the final year for the project. The first year saw our first pilot, a virtual experience surrounding the death of Elena Armova and the subsequent murder investigation. Two users were able to observe two police interrogations from behind a one way mirror. Taking on the role of savvy observant investigators, the users could discuss their view on the case with each other, while represented by Point Clouds or Time Varying Meshes. 

Pilot 2 undertaken in the second year pushed the boundaries of social VR and introduced a live component. Increasing the number of simultaneous users to 4, the users were made audience members of a live news broadcast on the subject of Armova’s shocking passing, and the mystery surrounding it. Combining various indoor and outdoor environments as well as content formats, users were offered the shared live experience of being together in a dynamic environment, while in reality the geographical separation could span the continent.

At the heart of the VR Together project lies the objective to enable social VR experiences with strong feelings of immersion as well as co-presence. To achieve this strong social sense of sharing a space together, photorealistic real-time representations of users are used, rather than relying on abstract avatars as found in such offerings as Facebook Spaces or AltspaceVR. Using state-of-the-art technologies developed by consortium partners and off-the-shelf hardware such as Microsoft Kinect or Intel RealSense sensors, users are scanned in real-time and the captured representations are processed and streamed as point clouds or time varying meshes (TVM). These approaches to user representation, combined with HMD removal technology, allow users sharing the virtual space – while in geographically separate locations – to see each other in all three dimensions.

Early feedback from users of the Pilot 1 demonstrations regarding the ability to see themselves and others, has been positive. The question still remains however, whether or not accurate self-representation has a significant positive impact on your sense of immersion, co-presence and the overall quality of experience. Both when seeing yourself as well as when interacting with others sharing the same virtual environment with you.

To answer this question, VR Together consortium partner Artanim will this summer run an experiment in which users will be placed in a virtual environment in which they are virtualized by a representation of themselves at varying levels of realism and likeness.

User representations will be created at 3 different levels of accuracy:

• An abstract avatar-like representation which does not match the participant
• A realistic representation of the participant
• An in-between more abstract – perhaps cartoon-like – representation of the participant, which is still recognizable, but steers clear of such undesirable effects as the “Uncanny Valley”.

To evaluate self-representation, single users will be placed in a virtual environment in which, by means of a virtual mirror, they will be able to observe themselves. The question there is whether or not an increased likeness improves the overall VR experience. To evaluate the importance of avatar likeness in the representation of others, pairs of users who know each other (i.e. friends or family) will share a virtual environment together, again being represented at varying levels of likeness. The goal there is to understand the effects on such aspects as immersion, togetherness and quality of interaction.

The proposed experiment will help us better understand what scenarios benefit most from realistic and recognizable user representation in Virtual Reality experiences, and to what extent realism is desirable in social VR.

With the rise of consumer VR and a wide range of VR headsets available, different means to produce and consume VR content are being used, such as 360 stereoscopic video and real time rendered 3D geometry. In this context, VR Together partners Artanim, Entropy and i2CAT are running an experiment to assess the quality of experience of users with the different forms of VR content representation.

The experiment will present the different versions of the interrogatory scene that Entropy and Artanim recorded and produced for Pilot 1 to participants in the study[CC1] . Actors were captured twice, once using a pair of cameras to produce stereo pairs for point of view video-based VR, and once using a professional whole-body motion capture pipeline, using their recorded animations to drive 3D meshes of the actors obtained with a custom photogrammetry-based reconstruction setup. Finally, three versions of the interrogatory were produced using the captured data: a 360 stereoscopic video (360 video); a mixture of 3D environment geometry and a character acting as a video billboard (3D environment + video characters); and a full 3D version (3D environment + 3D characters). The Table below demonstrates what the three content versions look like from a fixed point of view, and a top viewpoint to the scene: