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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Vydané v:	Journal of visual communication and image representation Ročník 67; s. 102747
Hlavní autori:	Yan, Mengjia, Meng, Jingjing, Zhou, Chunluan, Tu, Zhigang, Tan, Yap-Peng, Yuan, Junsong
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Inc 01.02.2020
Predmet:	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
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