Reliable multi-object tracking dealing with occlusions for a smart camera

Aziz Dziri, M. Duranton, R. Chapuis
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引用次数: 2

Abstract

In this paper, a multi-object tracking system designed for a low cost embedded smart camera is proposed. Objects tracking constitutes a main step in video-surveillance applications. Because of the number of cameras used to cover a large area, surveillance applications are constrained by the cost of each node, the power efficiency of the system, the robustness of the tracking algorithm and the real-time processing. They require a reliable multi-object tracking algorithm that can run in a real-time on light computing architectures. In this paper, we propose a tracking pipeline designed for a fixed smart camera that can handle occlusions between objects. We show that the proposed pipeline reaches real-time processing on the RaspberryPi board equipped with the RaspiCam camera. The tracking quality of the proposed pipeline is evaluated on publicly available datatsets: PETS2009 and CAVIAR.
智能相机处理遮挡的可靠多目标跟踪
提出了一种针对低成本嵌入式智能摄像机的多目标跟踪系统。目标跟踪是视频监控应用的主要步骤。由于使用的摄像机数量多,覆盖面积大,监控应用受到每个节点的成本、系统的功率效率、跟踪算法的鲁棒性和实时处理的限制。他们需要一个可靠的多目标跟踪算法,可以在轻计算架构上实时运行。在本文中,我们提出了一种用于固定智能相机的跟踪管道,可以处理物体之间的遮挡。我们证明了所提出的流水线在配备RaspiCam相机的RaspberryPi板上达到实时处理。拟议管道的跟踪质量在公开可用的数据集上进行评估:PETS2009和CAVIAR。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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