Probabilistic models have been previously shown to be efficient and effective for modeling and recognition of human motion. In particular we focus on methods which represent the h...
We develop a classification algorithm for hybrid autoregressive models of human motion for the purpose of videobased analysis and recognition. We assume that some temporal statist...
An appraisal of human motions and particular motion phases is essential for a good interaction between a human and a humanoid robot. We present a new method for the analysis of hum...
Estimating mode (walking/running/standing) and phases of human locomotion is important for video understanding. We present a new ”tracking as recognition” approach. A hierarch...
We present a new algorithm to generate plausible motions for high-DOF human-like articulated figures in constrained environments with multiple obstacles. Our approach is general ...
Jia Pan, Liangjun Zhang, Ming C. Lin, Dinesh Manoc...