We present a new scheme to robustly detect a type of human attentive behavior, which we call frequent change in focus of attention (FCFA), from video sequences. FCFA behavior can b...
The analysis of human action captured in video sequences has been a topic of considerable interest in computer vision. Much of the previous work has focused on the problem of acti...
The human figure exhibits complex and rich dynamic behavior that is both nonlinear and time-varying. However, most work on tracking and synthesizing figure motion has employed eit...
Vladimir Pavlovic, James M. Rehg, Tat-Jen Cham, Ke...
Activity and context recognition in pervasive and wearable computing ought to continuously adapt to changes typical of open-ended scenarios, such as changing users, sensor characte...
This paper presents a novel method to model and recognize human faces in video sequences. Each registered person is represented by a low-dimensional appearance manifold in the amb...