基于快速在线特征选择和分数水平融合的基于视图不变外观的人物再识别

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance Pub Date : 2012-09-18 DOI:10.1109/AVSS.2012.81

M. Eisenbach, Alexander Kolarow, Konrad Schenk, Klaus Debes, H. Groß

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引用次数: 27

摘要

快速、鲁棒的人员再识别是多摄像头监控和自动化门禁中的重要任务。我们提出了一种高效的基于外观的算法，能够重新识别一个人，而不受遮挡、与相机的距离、视角和光照的变化的影响。快速在线特征选择技术的使用使我们能够对多摄像头系统进行超实时的重新识别，只需10秒即可评估100分钟的高清视频数据。我们证明，我们的方法在再识别质量和计算速度方面超越了当前基于外观的最先进技术，并为非生物特征再识别提供了新的参考。

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View Invariant Appearance-Based Person Reidentification Using Fast Online Feature Selection and Score Level Fusion

Fast and robust person reidentification is an important task in multi-camera surveillance and automated access control. We present an efficient appearance-based algorithm, able to reidentify a person regardless of occlusions, distance to the camera, and changes in view and lighting. The use of fast online feature selection techniques enables us to perform reidentification in hyper-real-time for a multi-camera system, by taking only 10 seconds for evaluating 100 minutes of HD-video data. We demonstrate, that our approach surpasses current appearance-based state-of-the-art in reidentification quality and computational speed and sets a new reference in non-biometric reidentification.

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来源期刊

2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance

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