使用基于部件的混合描述符进行人员重新识别

2016 Second International Conference on Cognitive Computing and Information Processing (CCIP) Pub Date : 2016-08-01 DOI:10.1109/CCIP.2016.7802849

P. Sathish, S. Balaji

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引用次数: 1

摘要

实时人员再识别系统需要鲁棒描述符来提取有用的特征。本文研究了一种新的描述符，可以有效地重新识别不同视角和光照变化下的人物。描述符通过将人物图像分成多个部分来检测特征。我们使用局部和全局特征描述符的组合来形成一个可靠的描述符。性能评估是在基准测试数据集上完成的。

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Person re-identification using part based hybrid descriptor

Real time person re-identification systems require robust descriptors for useful feature extraction. This paper focuses on a novel descriptor which can efficiently re-identify persons in varied views and change in illumination. The descriptors detect the features by dividing the person image into multiple parts. We use a combination of local and global feature descriptors to form a reliable descriptor. Performance evaluation is done on a benchmarking dataset.

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2016 Second International Conference on Cognitive Computing and Information Processing (CCIP)

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