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題名: Abnormal Scene Change Detection from a Moving Camera Using Bags of Patches and Spider-Web Map
作者: Jun-Wei Hsieh
Chi-Hung Chuang
Salah Alghyaline
Hui-Fen Chiang
Chao-Hong Chiang
貢獻者: 國立臺灣海洋大學:資訊工程學系
NTOU:Department of Computer Science and Engineering
關鍵詞: Behavior analysis
abnormal scene change detection
pattern matching
video surveillance
日期: 2015-05
上傳時間: 2017-11-14T08:07:28Z
出版者: IEEE Sensors Journal
摘要: Abstract:This paper proposes a novel surveillance system for detecting exceptional scene changes as abnormal events with a mobile camera mounted on a robot. In contrast to abnormal event analysis using fixed cameras, three key problems should be tackled in this system, i.e., scene construction, robot localization, and scene comparison. For the first problem, scene construction, a clustering scheme is proposed for extracting a set of key frames from the surveillance environment. Each key frame is further divided into a set of patches, which forms a sparse representation for representing scene contents. In addition to the compression effect, the scheme can tackle the effects of misalignment and lighting changes well. For the localization problem, a novel patch matching method is proposed to reduce not only the size of the search space but also the size of the feature dimensions in similarity matching. To prune the search space, a set of projection kernels is used to construct a ring structure. Then, one order of time complexity in the similarity calculation can be reduced from the structure. After scene searching, the robot location is not always guaranteed to be successfully registered to the scene map. Thus, a novel spider-web map is proposed to tackle the effect of misalignment and then detect different exceptional scene changes from the videos. The proposed method has been rigorously tested on a variety of videos to demonstrate its superiority in object detection and abnormal scene change detection.
關聯: 15(5), pp.2866-2881
顯示於類別:[資訊工程學系] 期刊論文


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