کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
527856 869391 2012 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multi-scale and real-time non-parametric approach for anomaly detection and localization
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر چشم انداز کامپیوتر و تشخیص الگو
پیش نمایش صفحه اول مقاله
Multi-scale and real-time non-parametric approach for anomaly detection and localization
چکیده انگلیسی

In this paper we propose an approach for anomaly detection and localization, in video surveillance applications, based on spatio-temporal features that capture scene dynamic statistics together with appearance. Real-time anomaly detection is performed with an unsupervised approach using a non-parametric modeling, evaluating directly multi-scale local descriptor statistics. A method to update scene statistics is also proposed, to deal with the scene changes that typically occur in a real-world setting. The proposed approach has been tested on publicly available datasets, to evaluate anomaly detection and localization, and outperforms other state-of-the-art real-time approaches.


► 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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Vision and Image Understanding - Volume 116, Issue 3, March 2012, Pages 320–329
نویسندگان
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