The problem of recognizing actions in realistic videos
is challenging yet absorbing owing to its great potentials
in many practical applications. Most previous research is
limit...
Jintao Li, Ju Sun, Loong Fah Cheong, Shuicheng Yan...
In this paper, a new learning framework?probabilistic boosting-tree (PBT), is proposed for learning two-class and multi-class discriminative models. In the learning stage, the pro...
Human motion analysis has received a great attention from researchers in the last decade due to its potential use in different applications. We propose a new approach to extract h...
Actions in real world applications typically take place in cluttered environments with large variations in the orientation and scale of the actor. We present an approach to simult...
Probabilistic graphical models such as Bayesian Networks have been increasingly applied to many computer vision problems. Accuracy of inferences in such models depends on the quali...