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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Veröffentlicht in:	Journal of visual communication and image representation Jg. 67; S. 102747
Hauptverfasser:	Yan, Mengjia, Meng, Jingjing, Zhou, Chunluan, Tu, Zhigang, Tan, Yap-Peng, Yuan, Junsong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Inc 01.02.2020
Schlagworte:	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-Zugang:	Volltext
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