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首页> 外文会议>2013 Seventh International Conference on Distributed Smart Cameras >Occlusion management strategies for pedestrians tracking across fisheye camera networks
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Occlusion management strategies for pedestrians tracking across fisheye camera networks

机译：行人跨鱼眼镜头网络跟踪的遮挡管理策略

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摘要

This paper presents a particle filtering algorithm for multiple pedestrian objects tracking across fisheye cameras network. For this purpose, we first suggest a particle filter tracking algorithm that integrates a best view selection strategy to ensure tracking consistency across multiple cameras. The proposed best view selection strategy, based on a model describing the known static occluders of the scene, favors the view in which the static occlusion suffered by a partially occluded pedestrian object is the least severe. We propose to estimate the severity of a partial occlusion through a new metric, called visibility index. Secondly, to perform multi-pedestrian object tracking, we propose a framework in which multiple autonomous instances of the proposed particle filter are used, each filter tracking one specific pedestrian object and taking dynamic occlusions into account. The efficiency of the proposed distributed framework lies in the fact that it performs tracking in linear complexity in terms of the number of tracked objects.
机译：本文提出了一种用于鱼眼镜头网络中多个行人物体跟踪的粒子滤波算法。为此，我们首先建议一种粒子滤波跟踪算法，该算法集成了最佳视图选择策略，以确保跨多个摄像机的跟踪一致性。基于描述场景的已知静态遮挡物的模型，所提出的最佳视图选择策略偏向于这样的视图，在该视图中，部分遮挡的行人物体遭受的静态遮挡最不严重。我们建议通过一种称为可见性指标的新指标来估算部分遮挡的严重程度。其次，为了执行多行人目标跟踪，我们提出了一个框架，其中使用了所提出的粒子过滤器的多个自治实例，每个过滤器跟踪一个特定的行人对象并考虑了动态遮挡。所提出的分布式框架的效率在于以下事实：就所跟踪的对象的数量而言，它以线性复杂度执行跟踪。

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