In this paper we present a non-parametric approach to anomaly detection in surveillance videos. The real-time system uses spatio-temporal features, integrated in a multi-scale approach. The system can localize anomalies temporally (at frame level) and spatially (within frame). The systems has been compared to state-of-the-art approaches on a real-world UCSD dataset. According to experiments our method consistently outperforms other real-time approaches.
Multi-scale and real-time non-parametric approach for anomaly detection and localization / M. Bertini;A. Del Bimbo;L. Seidenari. - In: COMPUTER VISION AND IMAGE UNDERSTANDING. - ISSN 1077-3142. - STAMPA. - 116:(2012), pp. 320-329. [10.1016/j.cviu.2011.09.009]
Multi-scale and real-time non-parametric approach for anomaly detection and localization
M. Bertini;A. Del Bimbo;L. Seidenari
2012
Abstract
In this paper we present a non-parametric approach to anomaly detection in surveillance videos. The real-time system uses spatio-temporal features, integrated in a multi-scale approach. The system can localize anomalies temporally (at frame level) and spatially (within frame). The systems has been compared to state-of-the-art approaches on a real-world UCSD dataset. According to experiments our method consistently outperforms other real-time approaches.File | Dimensione | Formato | |
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