There has been a recent and increasing interest in computer analysis and recognition of human motion. Previously we presented an efficient real-time approach for representing huma...
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
In this paper we present a system for classifying various human actions in compressed domain video framework. We introduce the notion of quantifying the motion involved, through w...
Abstract. We propose motion manifold learning and motion primitive segmentation framework for human motion synthesis from motion-captured data. High dimensional motion capture date...
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...