使用积分通道功能的在线多人跟踪

2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS) Pub Date : 2016-08-01 DOI:10.1109/AVSS.2016.7738059

H. Kieritz, S. Becker, W. Hübner, Michael Arens

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引用次数: 95

摘要

在线多人跟踪受益于使用在线学习外观模型将检测与跟踪联系起来，并进一步缩小检测中的差距。由于积分通道特征(ICF)在快速行人检测中很受欢迎，我们提出了一种使用相同特征而无需重新计算的在线外观模型。该方法使用在线多实例学习(multi - instance Learning, MIL)对每个人与其周围环境的区别进行增量训练。我们表明，少量判别性选择的积分信道特征足以在MOT2015和MOT2016基准上获得最先进的结果。

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Online multi-person tracking using Integral Channel Features

Online multi-person tracking benefits from using an online learned appearance model to associate detections to tracks and further to close gaps in detections. Since Integral Channel Features (ICF) are popular for fast pedestrian detection, we propose an online appearance model that is using the same features without recalculation. The proposed method uses online Multiple-Instance Learning (MIL) to incrementally train an appearance model for each person discriminating against its surrounding. We show that a low number of discriminatingly selected Integral Channel Features are sufficient to achieve state-of-the-art results on the MOT2015 and MOT2016 benchmark.

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来源期刊

2016 13th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)

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