Anomaly detection in low quality traffic monitoring videos using optical flow

Jin Zhou; Chiman Kwan

doi:10.1117/12.2303651

30 April 2018 Anomaly detection in low quality traffic monitoring videos using optical flow

Jin Zhou, Chiman Kwan

Proceedings Volume 10649, Pattern Recognition and Tracking XXIX; 106490F (2018) https://doi.org/10.1117/12.2303651
Event: SPIE Defense + Security, 2018, Orlando, FL, United States

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.

Conference Presentation

Citation Download Citation

Jin Zhou and Chiman Kwan "Anomaly detection in low quality traffic monitoring videos using optical flow", Proc. SPIE 10649, Pattern Recognition and Tracking XXIX, 106490F (30 April 2018); https://doi.org/10.1117/12.2303651

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