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- 2017
利用人体部位特征重要性进行行人再识别
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Abstract:
提出了一种基于人体部位特征重要性的行人再识别算法，该算法首先提取人体各部位的颜色、纹理以及形状等特征，然后对多个行人样本的每个部位分别进行聚类分析，使用误差积累的方法为每个分类计算一种更适合该分类的部位特征重要性权值向量，使得不同类型特征能更有效地应用在其适合的外观上。在公共数据集VIPeR上进行了实验，通过积累匹配特性（cumulative matching characteristic，CMC）曲线对实验结果进行评价，结果表明，该算法具有较高的再识别率，且对行人视角转换、光照变化、环境嘈杂和物体遮挡有较好的鲁棒性
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