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Convoy Detection in Crowded Surveillance Videos

机译:拥挤监视视频中的车队检测

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This paper proposes detection of convoys in a crowded surveillance video. A convoy is defined as a group of pedestrians who are moving or standing together for a certain period of time. To detect such convoys, we firstly address pedestrian detection in a crowded scene, where small regions of pedestrians and their strong occlusions render usual object detection methods ineffective. Thus, we develop a method that detects pedestrian regions by clustering feature points based on their spatial characteristics. Then, positional transitions of pedestrian regions are analysed by our convoy detection method that consists of the clustering and intersection processes. The former finds groups of pedestrians in one frame by flexibly handling their relative spatial positions, and the latter refines groups into convoys by considering their temporal consistences over multiple frames. The experimental results on a challenging dataset shows the effectiveness of our convoy detection method.
机译:本文建议在拥挤的监控视频中检测车队。车队被定义为一组在一定时间段内一起移动或站立的行人。为了检测这种车队,我们首先在拥挤的场景中解决行人检测问题,在该场景中,行人的小区域及其强烈的遮挡使常规的物体检测方法无效。因此,我们开发了一种通过基于特征点的空间特征对特征点进行聚类来检测行人区域的方法。然后,通过我们的车队检测方法分析行人区域的位置过渡,该方法由聚类和交叉路口过程组成。前者通过灵活地处理行人的相对空间位置在一帧中找到行人群体,而后者通过考虑多个帧上的时间一致性将行人群体精化为车队。在具有挑战性的数据集上的实验结果表明了我们的车队检测方法的有效性。

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