Detecting spatiotemporal irregularities in videos via a 3D convolutional autoencoder

Spatiotemporal irregularities (i.e., the uncommon appearance and motion patterns) in videos are difficult to detect, as they are usually not well defined and appear rarely in videos. We tackle this problem by learning normal patterns from regular videos, while treating irregularities as deviations f...

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Bibliographic Details

Published in:	Journal of visual communication and image representation Vol. 67; p. 102747
Main Authors:	Yan, Mengjia, Meng, Jingjing, Zhou, Chunluan, Tu, Zhigang, Tan, Yap-Peng, Yuan, Junsong
Format:	Journal Article
Language:	English
Published:	Elsevier Inc 01.02.2020
Subjects:	3D convolution Anomaly detection Autoencoder Real-time Spatiotemporal irregularity detection Unsupervised learning Spatiotemporal irregularity detection 3D convolution Autoencoder Real-time Anomaly detection Unsupervised learning
ISSN:	1047-3203, 1095-9076
Online Access:	Get full text
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