Lyon & Harr, LLP
Mode-based multi-hypothesis tracking using parametric contours
A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.
Microsoft Corporation
G G G G G G G
G06V G06V G06T G06T G06V G06T G06T
inventional inventional additional inventional inventional inventional additional
Yong Yunqiang
Rui Chen