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Context-aware local abnormality detection in crowded scene

基于上下文感知的拥挤场景局部异常检测

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Abstract

In this paper, we propose a novel algorithm by jointly modeling motion and context information targeting at detecting abnormal events in crowded scenes. In our algorithm, context pattern information, extracted through volume local binary patterns computation on three orthogonal planes (LBP-TOP) between local target areas with surrounding areas, is explicitly taken into consideration for localizing abnormality. To capture motion information, a novel feature descriptor named Multi-scale Histogram of Frequency Coefficient is explored by taking Fourier Transform on the extracted dense trajectories. For detection of abnormality, sparse reconstruction cost from a learned event dictionary is adopted to classify local normal and abnormal events. Experiments conducted on three benchmark datasets show superior performance to many related state-of-the-art methods.

摘要

创新点

本论文通过对运动特征和上下文感知联合建模, 提出了一种新颖的算法用于拥挤场景下的异常事件检测。 在本算法中, 通过目标区域和周围区域的三个交叉垂直平面计算时空局部二值模式信义, 以提取上下文信息, 用于精确定位异常事件位置。 另外, 通过稠密轨迹的傅里叶变换系数, 提取则多尺度频率系数直方图用于运动特征。 最后基于已训练字典的重构误差来判别异常事件。 本算法, 在三个基准数据上取得很好效果, 证明了算法的有效性。

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Author information

Authors and Affiliations

  1. Beijing Technology and Business University, Beijing, 100048, China

    XiaoBin Zhu

  2. Beijing Electronic Science and Technology Institute, Beijing, 100070, China

    Xin Jin

  3. Institute of Information Engineering, Chinese Academy of Sciences, Beijing, 100093, China

    XiaoYu Zhang

  4. IBM Research-China, Beijing, 100193, China

    ChangSheng Li

  5. People’s Public Security University of China, Beijing, 100038, China

    FuGang He

  6. Academy of Broadcasting Science, State Administration of Press, Publication, Radio, Film and Television of The People’s Republic of China (SARFT), Beijing, 100866, China

    Lei Wang

  7. Information Technology Research Base of Civil Aviation Administration of China, Civil Aviation University of China, Tianjin, 300300, China

    Xin Jin

Authors
  1. XiaoBin Zhu
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  2. Xin Jin
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  3. XiaoYu Zhang
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  4. ChangSheng Li
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  5. FuGang He
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  6. Lei Wang
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Correspondence to Xin Jin or XiaoYu Zhang.

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Zhu, X., Jin, X., Zhang, X. et al. Context-aware local abnormality detection in crowded scene. Sci. China Inf. Sci. 58, 1–11 (2015). https://doi.org/10.1007/s11432-015-5294-x

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  • DOI: https://doi.org/10.1007/s11432-015-5294-x

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