Do you feel in control of the body that you see? This is an important question in virtual reality (VR) as it highly impacts the user’s sensation of presence and embodiment of an avatar representation while immersed in a virtual environment. To better understand this aspect, we performed an experiment in the framework of the VR-Together project to assess the relative impact of different levels of body animation fidelity to presence.
In this experiment, the users are equipped with a motion capture suit and reflective markers to track their movements in real time with a Vicon optical motion capture system. They also wear Manus VR gloves for fingers tracking and an Oculus HMD. At each trial, the face (eye gaze and mouth), fingers and the avatar’s upper and lower bodies are manipulated with different degree of animation fidelity, such as no animation, procedural animation and motion capture. Each time, users have to execute a number of tasks (walk, grab an object, speak in front of a mirror) and to evaluate if they are in control of their body. Users start with the simplest setting and, according to the judged priority, improve features of the avatar animation until they are satisfied with the experience of control.
Using the order in which users improve the movement features, we can assert on the most valuable animation features to the users. With this experiment, we want to confront the relative importance of animation features with the costs of adoption (monetary and effort) to provide software and use guidelines for live 3D rigged character mesh animation based on affordable hardware. This outcome will be useful to better define what makes a compelling social VR experience.
Artanim collaborated with Entropy Studio on the shooting of the first pilot of the VR-Together project. After a short flight from Madrid to Geneva, the actors were 3D scanned with our photogrammetric scanner consisting of 96 cameras, to obtain the 3D surface of their body. Steve Galache (known for his work on The Vampire in the Hole, 2010; El cosmonauta, 2013; and Muertos comunes, 2004), Jonathan David Mellor (known for The Wine of Summer, 2013; Refugiados, 2014; and [Rec]², 2009) and Almudena Calvo were the main characters of this first experience. They were dressed the same way as in the shooting scene.
The shooting was split over two days. The first day was dedicated to shoot the actors in costumes on a complete chroma background with a stereo-camera. This will allow the creation of photoreal stereo-billboards that will be integrated in a full CG-environment. The second day of shooting was focused on full performance capture of the actors. Each equipped with 59 retro-reflective markers and an head-mounted iPhone X, the actors were able to perform the investigation plot (an interrogatory scene) with success. These data will later be used to animate the 3D models of the actors generated from the 3D scans. These full-CG models will be finally integrated in the same virtual environment.
This pilot project will thus offer two different rendering modalities for real actors (stereo-bilboard and CG characters). The impact of both techniques will be studied through user studies with an eye on social presence and immersion.
We will soon start shooting cinematic content to be used for showcasing the technology developed by the VR-Together consortium. In this post, we bring some of the production effort developed at Artanim, which is currently exploring the use of Apple’s iPhone X face tracking technology in the production pipeline of 3D animations.
The photos below show the iPhone X holding rig, and an early version of the face tracking recording tool that was developed by Artanim. The tool integrates with full body and hands motion capture technology from Vicon to allow the simultaneous recording of body, hands and face performance from multiple actors.
With the recent surge of consumer virtual reality, interest for motion capture has dramatically increased. The iPhone X and ARKit SDK from Apple integrate depth sensing and facial animation technologies, and are a good example of this trend. Apple’s effort to integrate advanced face tracking to their mobile devices may be related to the recent acquisition of PrimeSense and FaceShift. The former was involved in the development of the technology powering the first Kinect back in 2011, the latter is recognized for their face tracking technology, which is briefly showcased in the making of Star Wars: The Force Awakens trailer. These are exciting times, when advanced motion tracking technologies are becoming ubiquitous in our life.
Image from the iPhone X keynote presentation from Apple
Artanim has just moved its offices in Meyrin located only minutes away from the city center and with easy access to the highway, the train station and the International Airport of Geneva. Artanim is now housed within a facility of 273 m2 with a capture stage twice bigger than before. The facility includes offices and a conference room, a sound/post-production studio and a wardrobe/make-up room with shower.
On December 15th, we inaugurated our new offices with our friends, colleagues and partners. For the occasion, we organized a real time dance performance using our Xsens suit in collaboration with the Cie Gilles Jobin (dancer: Susana Panadés Diaz).
Artanim just added a new tool to its motion capture equipment: the Optitrack Insight VCS, a professional virtual camera system. From now on, everyone doing motion capture at Artanim will be able to step into the virtual set, preview or record real camera movement and find the best angles to view the current scene.
The motion capture data captured by our Vicon system is processed in real time in MotionBuilder and displayed on the camera monitor. The position of MotionBuilder’s virtual camera is updated by the position of the reflective markers on the camera rig. In addition, the camera operator can control several parameters such as the camera zoom, horizontal panning, etc. The rig itself is very flexible and can be modified to accommodate different shooting styles (shoulder-mounted, hand-held, etc.).
We can’t wait to use it in future motion capture sessions and show you some results. Meanwhile, you can have a look at our first tests in the above video.
🧍 HUMAN4D dataset provides a diverse set of motions and poses encountered as part of single- and multi-person daily, physical and social activities, along with multi-RGBD (mRGBD), volumetric and audio data.