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题名: Suspicious object detection using fuzzy-color histogram
作者: Chi-Hung Chuang
Jun-Wei Hsieh
Luo-Wei Tsai
Pei-Shiuan Ju
Kao-Chin Fan
贡献者: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
关键词: Object detection
Event detection
Hidden Markov models
Motion detection
Video sequences
日期: 2008-05
上传时间: 2017-11-14T08:49:30Z
出版者: 2008 IEEE International Symposium on Circuits and Systems
摘要: Abstract:This paper proposes a novel method to detect suspicious objects from videos for abnormal event analysis. When considering a robbery event happens, there should be some suspicious object transferring conditions following between the forager and the victim. Since there is no prior knowledge about the object’s property, it is difficult to automatically analyze the conditions without any manual efforts. To tackle this problem, a ratio histogram based on fuzzy c-means algorithm is proposed for finding suspicious objects. Furthermore, we use Gaussian mixture models to model the suspicious object’s visual properties so that it can be accurately segmented from videos. After analyzing its subsequent motion features, different abnormal events like robbery can be effectively detected from videos. Experiment results have proved that the proposed method is robust, accurate, and powerful in abnormal event detection.
显示于类别:[資訊工程學系] 演講及研討會


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