We propose a space-time Markov Random Field (MRF)
model to detect abnormal activities in video. The nodes in
the MRF graph correspond to a grid of local regions in the
video fra...
Jaechul Kim (University of Texas at Austin), Krist...
Human action in video sequences can be seen as silhouettes of a moving torso and protruding limbs undergoing articulated motion. We regard human actions as three-dimensional shapes...
Moshe Blank, Lena Gorelick, Eli Shechtman, Michal ...
A novel technique to detect and localize periodic movements in video is presented. The distinctive feature of the technique is that it requires neither feature tracking nor object...
The notion of local features in space-time has recently been proposed to capture and describe local events in video. When computing space-time descriptors, however, the result may...
Recent work shows how to use local spatio-temporal features to learn models of realistic human actions from video. However, existing methods typically rely on a predefined spatial...