We present a method for efficiently generating a representation of a multi-modal posterior probability distribution. The technique combines ideas from RANSAC and particle filterin...
For applications such as video surveillance and human computer interface, we propose an efficiently integrated method to detect and track faces. Various visual cues are combined t...
Tae-Kyun Kim, Sung-Uk Lee, Jong Ha Lee, Seok-Cheol...
This paper presents a Bayesian network based multimodal fusion method for robust and real-time face tracking. The Bayesian network integrates a prior of second order system dynami...
We present a Dynamic Data Driven Application System (DDDAS) to track 2D shapes across large pose variations by learning non-linear shape manifold as overlapping, piecewise linear s...
Abstract. Visual detection and tracking of humans in complex scenes is a challenging problem with a wide range of applications, for example surveillance and human-computer interact...
ZhenQiu Zhang, Gerasimos Potamianos, Andrew W. Sen...