Real-time control of human actions using inertial sensors
- 178 Downloads
Our study proposes a new local model to accurately control an avatar using six inertial sensors in real-time. Creating such a system to assist interactive control of a full-body avatar is challenging because control signals from our performance interfaces are usually inadequate to completely determine the whole body movement of human actors. We use a pre-captured motion database to construct a group of local regression models, which are used along with the control signals to synthesize whole body human movement. By synthesizing a variety of human movements based on actors’ control in real-time, this study verifies the effectiveness of the proposed system. Compared with the previous models, our proposed model can synthesize more accurate results. Our system is suitable for common use because it is much cheaper than commercial motion capture systems.
Keywordsavatars motion capture/editing/synthesis interaction techniques game interaction animation simulation
Unable to display preview. Download preview PDF.
- 1.Badler N I, Hollick M, Granieri J. Realtime control of a virtual human using minimal sensors. Presence, 1993, 2: 82–86Google Scholar
- 3.Yin K, Pai D K. FootSee: an interactive animation system. In: Proceedings of the 2003 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, San Diego, 2003. 329–338Google Scholar
- 4.Slyper R, Hodgins J. Action capture with accelerometers. In: Proceedings of 2008 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, Dublin, 2008. 193–199Google Scholar
- 7.Liu H J, Wei X L, Chai J X, et al. Realtime human motion control with a small number of inertial sensors. In: Proceedings of the 2011 Symposium on Interactive 3D Graphics and Games. New York: ACM, 2011. 133–140Google Scholar
- 8.Shotton J, Fitzgibbon A, Cook M, et al. Real-time human pose recognition in parts from single depth images. In: Proceedings of the IEEE International Conference on Computer Vision and Pattern Recognition. Washington DC: IEEE Computer Society, 2011. 1297–1304Google Scholar
- 11.Kwon T, Shin S Y. Motion modeling for online locomotion synthesis. In: ACM SIGGRAPH/Eurographics Symposium on Computer Animation, Los Angeles, 2005. 29–38Google Scholar
- 15.Lee Y, Wampler K, Bernstein G, et al. Motion fields for interactive character locomotion. ACM Trans Graph, 2010, 29: 1–8Google Scholar
- 24.Wei X L, Min J Y, Chai J X. Physically valid statistical models for human motion generation. ACM Trans Graph, 2011, 30: 19Google Scholar