This work investigates the use of nonlinear dependencies in natural image sequence statistics to learn higher-order structures in natural videos. We propose a two-layer model that...
While traditional face recognition is typically based on still images, face recognition from video sequences has become popular recently. In this paper, we propose to use adaptive...
We present a study on the use of soft computing techniques for object tracking/segmentation in surveillance video clips. A number of artificial creatures, conceptually, "inhab...
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 ...
This work addresses the challenge of extracting structure in educational and training media based on the type of material that is presented during lectures and training sessions. ...