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...
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Current work in object categorization discriminates
among objects that typically possess gross differences
which are readily apparent. However, many applications
require making ...
Andrew Moldenke, Asako Yamamuro, David A. Lytle, E...
Boosting has become very popular in computer vision, showing impressive performance in detection and recognition tasks. Mainly off-line training methods have been used, which impl...
In this paper we develop a system for human behaviour recognition in video sequences. Human behaviour is modelled as a stochastic sequence of actions. Actions are described by a f...