A modular tracking system for far infrared pedestrian recognition

IEEE Proceedings. Intelligent Vehicles Symposium, 2005. Pub Date : 2005-06-06 DOI:10.1109/IVS.2005.1505196

E. Binelli, A. Broggi, A. Fascioli, S. Ghidoni, P. Grisleri, Thorsten Dr. Graf, M. Meinecke

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引用次数: 46

Abstract

This paper describes a modular tracking system designed to improve the performance of a pedestrian detector. The tracking system consists of two modules, a labeler and a predictor. The former associates a tracking identifier to each pedestrian, keeping memory of the past history; this is achieved by merging the detector and predictor outputs combined with data about vehicle motion. The predictor, basically a Kalman filter, estimates the new pedestrian position by observing his previous movements. Its output helps the labeler to improve the match between the pedestrians detected in the new frame and those observed in the previous shots (feedback). If a pedestrian is occluded by some obstacle for a short while, the system continues tracking its movement using motion parameters. Moreover, it is able to reassign the same tracking ID in case the occlusion disappears in a short time. This behavior helps to correct temporary mis-recognitions that occur when the detector fails. The system has been tested using a quantitative performance evaluation tool, giving promising results.

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一种用于远红外行人识别的模块化跟踪系统

本文介绍了一种模块化跟踪系统，旨在提高行人检测器的性能。跟踪系统由两个模块组成，一个标签器和一个预测器。前者给每一个行人都配上一个追踪标识，保持对过去历史的记忆;这是通过将检测器和预测器输出与车辆运动数据相结合来实现的。预测器基本上是一个卡尔曼滤波器，通过观察行人之前的动作来估计新的行人位置。它的输出帮助标注器改善新帧中检测到的行人与之前镜头中观察到的行人之间的匹配(反馈)。如果行人被障碍物阻挡了一小段时间，系统会使用运动参数继续跟踪其运动。此外，它能够在遮挡在短时间内消失的情况下重新分配相同的跟踪ID。这种行为有助于纠正检测器失效时出现的临时错误识别。该系统已使用定量性能评估工具进行了测试，结果令人满意。

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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IEEE Proceedings. Intelligent Vehicles Symposium, 2005.

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