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Anomaly detection in low quality traffic monitoring videos using optical flow
Author(s): Jin Zhou; Chiman Kwan
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Paper Abstract

This paper summarizes a preliminary study on anomaly detection in low quality traffic monitoring videos. An optical flow based anomaly detection algorithm is proposed to detect anomalies in videos. The algorithm is efficient. Preliminary experiments demonstrate that the proposed algorithm is feasible and has good performance. It should be noted that the anomaly detection algorithm can be used to generate video summaries where the start and end times of anomalies are recorded. In addition, we also developed a user friendly tool that can help operators review video summaries.

Paper Details

Date Published: 30 April 2018
PDF: 11 pages
Proc. SPIE 10649, Pattern Recognition and Tracking XXIX, 106490F (30 April 2018); doi: 10.1117/12.2303651
Show Author Affiliations
Jin Zhou, Signal Processing, Inc. (United States)
Chiman Kwan, Signal Processing, Inc. (United States)


Published in SPIE Proceedings Vol. 10649:
Pattern Recognition and Tracking XXIX
Mohammad S. Alam, Editor(s)

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