Abnormal Event Detection via Multikernel Learning for Distributed Camera Networks

Tian Wang, Jie Chen, Paul Honeine, Hichem Snoussi

科研成果: 期刊稿件文章同行评审

6 引用 (Scopus)

摘要

Distributed camera networks play an important role in public security surveillance. Analyzing video sequences from cameras set at different angles will provide enhanced performance for detecting abnormal events. In this paper, an abnormal detection algorithm is proposed to identify unusual events captured by multiple cameras. The visual event is summarized and represented by the histogram of the optical flow orientation descriptor, and then a multikernel strategy that takes the multiview scenes into account is proposed to improve the detection accuracy. A nonlinear one-class SVM algorithm with the constructed kernel is then trained to detect abnormal frames of video sequences. We validate and evaluate the proposed method on the video surveillance dataset PETS.

源语言英语
文章编号989450
期刊International Journal of Distributed Sensor Networks
2015
DOI
出版状态已出版 - 2015

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