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Object and patch based anomaly detection and localization in crowded scenes

机译：对象和贴片基于拥挤场景的异常检测和本地化

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摘要

Detecting and localizing anomalies in crowded scenes is an ongoing challenge for public security. Existing approaches are mainly based on patches and trajectories. However, they fall short in semantic understanding of scenes and tackling the depth-of-field problem, respectively. In this paper, we put forward a novel object and patch based framework for anomaly detection and localization. Specifically, we propose to colorize images for precise object detection in dim scenarios. Categories of the objects are used for appearance anomaly justification. For motion anomaly, we propose a new patch-based algorithm which is robust to the depth-of-field problem, which can also be used to detect location anomalies. Besides, a new object re-targeting method is proposed to find the missing objects in detection. It can also handle drift and occlusions in tracking, which can avoid false alarms. Extensive experiments are conducted on several benchmark datasets for anomaly detection. The results show that the proposed method can achieve comparable accuracy in anomaly detection with state-of-the-arts methods and at the same time, localize anomalies precisely.
机译：检测和定位拥挤场景中的异常是公共安全的持续挑战。现有方法主要基于斑块和轨迹。然而，它们分别在语义理解中缩短，并分别解决场景深度问题。在本文中，我们提出了一种新的对象和基于贴片的异常检测和定位框架。具体而言，我们建议在暗淡方案中彩色图像以进行精确对象检测。物品类别用于外观异常理由。对于运动异常，我们提出了一种新的基于补丁的算法，它对场的深度问题很稳健，这也可用于检测位置异常。此外，提出了一种新的对象重新定位方法来找到检测中缺失的对象。它还可以处理跟踪中的漂移和闭塞，这可以避免误报。在几个基准数据集上进行了广泛的实验，用于异常检测。结果表明，该方法可以通过最先进的方法实现异常检测的可比精度，同时，精确定位异常。

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  • 来源
    《Multimedia Tools and Applications》 |2019年第15期|21375-21390|共16页
  • 作者

    Li Xiaodan; Li Weihai; Liu Bin; Yu Nenghai;

  • 作者单位

    Univ Sci & Technol China Sch Informat Sci & Technol Hefei Anhui Peoples R China|Chinese Acad Sci Key Lab Electromagnet Space Informat Hefei Anhui Peoples R China;

    Univ Sci & Technol China Sch Informat Sci & Technol Hefei Anhui Peoples R China|Chinese Acad Sci Key Lab Electromagnet Space Informat Hefei Anhui Peoples R China;

    Univ Sci & Technol China Sch Informat Sci & Technol Hefei Anhui Peoples R China|Chinese Acad Sci Key Lab Electromagnet Space Informat Hefei Anhui Peoples R China;

    Univ Sci & Technol China Sch Informat Sci & Technol Hefei Anhui Peoples R China|Chinese Acad Sci Key Lab Electromagnet Space Informat Hefei Anhui Peoples R China;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Anomaly; Object; Colorizing; Patch; Re-targeting;

    机译：异常;物体;着色;补丁;重新定位;

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