Abnormal event detection based on appearance repair and motion consistency

Lunzheng Tan; Cheng He

doi:10.1117/12.2662614

28 December 2022 Abnormal event detection based on appearance repair and motion consistency

Lunzheng Tan, Cheng He

Author Affiliations +

Proceedings Volume 12506, Third International Conference on Computer Science and Communication Technology (ICCSCT 2022); 125063U (2022) https://doi.org/10.1117/12.2662614
Event: International Conference on Computer Science and Communication Technology (ICCSCT 2022), 2022, Beijing, China

Abstract

The application of abnormal event detection in video surveillance is an active research field, but due to the imbalance of positive and negative samples in surveillance video, abnormal event detection is full of challenges. In this paper, we propose a new abnormal event detection method based on appearance repair and motion consistency for detecting anomalous events. Specifically, the input image is partially masked and then fed into our proposed appearance repair autoencoder for image reconstruction, and then the motion consistency of images is constructed by our proposed optical flow network. The experimental results on the UCSD, CUHK Avenue datasets show the superiority of the detection performance of our method.

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Lunzheng Tan and Cheng He "Abnormal event detection based on appearance repair and motion consistency", Proc. SPIE 12506, Third International Conference on Computer Science and Communication Technology (ICCSCT 2022), 125063U (28 December 2022); https://doi.org/10.1117/12.2662614

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