Published:
May 2004
Proceedings:
Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2004)
Volume
Issue:
Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2004)
Track:
All Papers
Downloads:
Abstract:
Novelty detection in video is a rapidly developing application domain within computer vision. The motivation behind this paper is a learning based framework for detecting novelty within video. Since, humans have a general understanding about their environment and possess a sense of distinction between what is normal and abnormal about the environment based on our prior experience; any aspect of the scene that does not fit into this definition of normalcy tends to be labeled as a novel event. In this paper, we propose a computational learning based framework for novelty detection and provide the experimental evidence to describe the results obtained by this framework. To begin with the framework extracts low-level features from scenes, based on the focus of attention theory and then combines unsupervised learning techniques such as clustering with habituation theory to emulate the cognitive aspect of learning.
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FLAIRS
Proceedings of the Seventeenth International Florida Artificial Intelligence Research Society Conference (FLAIRS 2004)
ISBN 978-1-57735-201-3
Published by The AAAI Press, Menlo Park, California.