Abnormal Scene Change Detection from a Moving Camera Using Bags of Patches and Spider-Web Map

Jun-Wei Hsieh, Chi Hung Chuang, Salah Alghyaline, Hui Fen Chiang, Chao Hong Chiang

研究成果: Article同行評審

15 引文 斯高帕斯(Scopus)


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.

頁(從 - 到)2866-2881
期刊IEEE Sensors Journal
出版狀態Published - 26 5月 2015


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