Video anomaly detection and localization via Gaussian Mixture Fully Convolutional Variational Autoencoder

We present a novel end-to-end partially supervised deep learning approach for video anomaly detection and localization using only normal samples. The insight that motivates this study is that the normal samples can be associated with at least one Gaussian component of a Gaussian Mixture Model (GMM),...

Celý popis

Podrobná bibliografia

Vydané v:	Computer vision and image understanding Ročník 195; s. 102920
Hlavní autori:	Fan, Yaxiang, Wen, Gongjian, Li, Deren, Qiu, Shaohua, Levine, Martin D., Xiao, Fei
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Elsevier Inc 01.06.2020
Predmet:	Anomaly detection Dynamic flow Gaussian mixture model Two-stream network Variational autoencoder Video surveillance Variational autoencoder Video surveillance Dynamic flow Two-stream network Anomaly detection Gaussian mixture model
ISSN:	1077-3142, 1090-235X
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!