Avatars Grow Legs: Generating Smooth Human Motion from Sparse Tracking Inputs with Diffusion Model
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
ACM Symposium on Applied Perception (SAP)
Social virtual reality uses motion tracking to place people in virtual environments as animated avatars. Often this tracking only measures the position and orientation of the head and hands, and from this estimates the body pose. Optical hand tracking is an important technology to enable such avatars, but can frequently fail and cause motion errors when the hands are visually obscured. This paper presents three amelioration strategies to handle these errors and demonstrates experimentally that all three are effective in reducing their impact. This setting is also used to explore general issues around study design for motion perception. Different strategies for presenting stimuli and soliciting input are compared. The presence of a simultaneous recall task is shown to reduce but not eliminate sensitivity to motion errors. Finally, it is shown that motion errors are interpreted, at least in part, as a shift in interlocutor personality.
Yuming Du, Robin Kips, Albert Pumarola, Sebastian Starke, Ali Thabet, Artsiom Sanakoyeu
Bilge Acun, Benjamin Lee, Fiodar Kazhamiaka, Kiwan Maeng, Manoj Chakkaravarthy, Udit Gupta, David Brooks, Carole-Jean Wu
Giovanni Apruzzese, Hyrum S. Anderson, Savino Dambra, David Freeman, Fabio Pierazzi, Kevin Roundy