This paper proposes a metric learning based approach for human activity recognition with two main objectives: (1) reject unfamiliar activities and (2) learn with few examples. We s...
We take advantage of the temporal continuity in an iris video to improve matching performance using signal-level fusion. From multiple frames of an iris video, we create a single a...
Karen Hollingsworth, Kevin W. Bowyer, Patrick J. F...
The objective of this work is to identify some of the traffic characteristics of Wireless Multimedia Sensor Networks (WMSN). Applications such as video surveillance sensor networks...
We present a probabilistic reliable-inference framework to address the issue of rapid detection of human actions with low error rates. The approach determines the shortest video e...
We propose a method for recognizing human actions in videos. Inspired from the recent bag-of-words approaches, we represent actions as documents consisting of words, where a word ...