Dynamic video anomaly detection and localization using sparse denoising autoencoders

The emergence of novel techniques for automatic anomaly detection in surveillance videos has significantly reduced the burden of manual processing of large, continuous video streams. However, existing anomaly detection systems suffer from a high false-positive rate and also, are not real-time, which...

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Vydané v:	Multimedia tools and applications Ročník 77; číslo 11; s. 13173 - 13195
Hlavní autori:	Narasimhan, Medhini G., S., Sowmya Kamath
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Springer US 01.06.2018 Springer Nature B.V
Predmet:	Anomalies Computer Communication Networks Computer Science Computing time Data Structures and Information Theory Datasets Deep learning Dictionaries Localization Machine learning Multimedia Information Systems Noise reduction Special Purpose and Application-Based Systems Surveillance Teaching methods Video data Deep learning Crowded scene parsing Sparse autoencoders Real-time systems Anomaly detection Unsupervised learning
ISSN:	1380-7501, 1573-7721
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