Most model based rate control solutions have the generally questionable assumption that video sequence is stationary, and also suffer from the fundamental problems of model parame...
In this work, we address a method that is able to track simultaneously 3D head movements and facial actions like lip and eyebrow movements in a video sequence. In a baseline frame...
We describe a probabilistic framework for recognizing human activities in monocular video based on simple silhouette observations in this paper. The methodology combines kernel pr...
Abstract. Detecting abnormal event from video sequences is an important problem in computer vision and pattern recognition and a large number of algorithms have been devised to tac...
In this paper, we present a Deformable Action Template
(DAT) model that is learnable from cluttered real-world
videos with weak supervisions. In our generative model,
an action ...