Interactive tracking-based pedestrian segmentation in dynamic scenes

Xiang Xiang
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Abstract

Moving object segmentation is highly beneficial to human identification and behavior analysis in intelligent video surveillance. The widely-used background subtraction works not well in dynamic scenes. In this paper, the problem is addressed by first localizing the object by tracking and then segmenting it locally via Graph cuts. We also propose a robust tracker combining the merits of two existing methods [1] and [2], and display an interactive segmentation system. Experiments verify the feasibility of our method and that the proposed tracker outperforms most state-of-the-art methods.
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动态场景中基于交互式跟踪的行人分割
在智能视频监控中,运动目标分割对人的识别和行为分析有很大的帮助。广泛使用的背景减法在动态场景中效果不佳。在本文中,首先通过跟踪来定位对象,然后通过图切割对其进行局部分割。我们还提出了一种鲁棒跟踪器,结合了两种现有方法[1]和[2]的优点,并展示了一个交互式分割系统。实验验证了我们的方法的可行性,并且所提出的跟踪器优于大多数最先进的方法。
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