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Deep Appearance Features for Abnormal Behavior Detection in Video

2017; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-319-68548-9_70

1611-3349

Sorina Smeureanu, Radu Tudor Ionescu, Marius Popescu, Bogdan Alexe,

Digital Media Forensic Detection

We propose a novel framework for abnormal event detection in video that is based on deep features extracted with pre-trained convolutional neural networks (CNN). The CNN features are fed into a one-class Support Vector Machines (SVM) classifier in order to learn a model of normality from training data. We compare our approach with several state-of-the-art methods on two benchmark data sets, namely the Avenue data set and the UMN data set. The empirical results indicate that our abnormal event detection framework can reach state-of-the-art results, while running in real-time at 20 frames per second.