ControllerPose: Inside-Out Body Capture with VR Controller Cameras

要旨

We present a new and practical method for capturing user body pose in virtual reality experiences: integrating cameras into handheld controllers, where batteries, computation and wireless communication already exist. By virtue of the hands operating in front of the user during many VR interactions, our controller-borne cameras can capture a superior view of the body for digitization. Our pipeline composites multiple camera views together, performs 3D body pose estimation, uses this data to control a rigged human model with inverse kinematics, and exposes the resulting user avatar to end user applications. We developed a series of demo applications illustrating the potential of our approach and more leg-centric interactions, such as balancing games and kicking soccer balls. We describe our proof-of-concept hardware and software, as well as results from our user study, which point to imminent feasibility.

著者
Karan Ahuja
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Vivian Shen
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Cathy Mengying Fang
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Nathan Riopelle
Human-Computer Interaction Institute, Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Andy Kong
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
Chris Harrison
Carnegie Mellon University, Pittsburgh, Pennsylvania, United States
論文URL

https://dl.acm.org/doi/abs/10.1145/3491102.3502105

動画

会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2022.acm.org/)

セッション: Let's get Physical

290
5 件の発表
2022-05-04 18:00:00
2022-05-04 19:15:00