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Abnormal Event Detection in Video Using Motion and Appearance Information
Journal
Lecture Notes in Computer Science
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Date Issued
2018
Author(s)
Guillermo Cámara Chávez
DOI
http://dx.doi.org/10.1007/978-3-319-75193-1_46
Abstract
This paper presents an approach for the detection and localization of abnormal events in pedestrian areas. The goal is to design a model to detect abnormal events in video sequences using motion and appearance information. Motion information is represented through the use of the velocity and acceleration of optical flow and the appearance information is represented by texture and optical flow gradient. Unlike literature methods, our proposed approach provides a general solution to detect both global and local abnormal events. Furthermore, in the detection stage, we propose a classification by local regions. Experimental results on UMN and UCSD datasets confirm that the detection accuracy of our method is comparable to state-of-the-art methods.
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