Tracking-as-Recognition for Articulated Full-Body Human Motion Analysis

Patrick Peursum, Svetha Venkatesh, Geoff West
2007 2007 IEEE Conference on Computer Vision and Pattern Recognition  
This paper addresses the problem of markerless tracking of a human in full 3D with a high-dimensional (29D) body model. Most work in this area has been focused on achieving accurate tracking in order to replace marker-based motion capture, but do so at the cost of relying on relatively clean observing conditions. This paper takes a different perspective, proposing a body-tracking model that is explicitly designed to handle real-world conditions such as occlusions by scene objects, failure
more » ... ects, failure recovery, long-term tracking, auto-initialisation, generalisation to different people and integration with action recognition. To achieve these goals, an action's motions are modelled with a variant of the hierarchical hidden Markov model. The model is quantitatively evaluated with several tests, including comparison to the annealed particle filter, tracking different people and tracking with a reduced resolution and frame rate.
doi:10.1109/cvpr.2007.383130 dblp:conf/cvpr/PeursumVW07 fatcat:2kq7jcpg7bbondi2jd6sjl2myu