| 利用人体部位特征重要性进行行人再识别 |
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| 引用本文： | 章登义,王骞,朱波,武小平,曹瑀,蔡波.利用人体部位特征重要性进行行人再识别[J].武汉大学学报(信息科学版),2017,42(1):84-90. |
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| 作者姓名： | 章登义 王骞 朱波 武小平 曹瑀 蔡波 |
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| 作者单位： | 1.武汉大学计算机学院, 湖北 武汉, 430072 |
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| 基金项目： | 湖北省科技支撑计划2014BAA149 |
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| 摘 要： | 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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| 关 键 词： | 视频监控 行人再识别 部位特征重要性 聚类分析 CMC曲线 |
| 收稿时间： | 2016-04-30 |
Person Re-identification Based on Part Feature Importance |
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| Institution: | 1.School of Computer, Wuhan University, Wuhan 430072, China2.Wuhan Land Resources and Planning Information Center, Wuhan 430014, China |
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| Abstract: | In a video surveillance system, same person may looks different across different camera, while different people may look the same in one camera, thus making person re-identification a challenging problem. This paper carried out an algorithm based on part feature importance, firstly extract features such as color, texture and shape. Then cluster each part by classify different appearance of body parts, using an error accumulation method to figure out weight vector indicate the significant of the feature, which fit the type of appearance. Calculating the similarity at last, using this vector to weighting the features of each part, making the feature more suitable for the appearance. This algorithm indicate some features are more important than others for parts with different appearance. We had complete our experiments on the public datasets VIPeR, and evaluate the result by CMC curve, which indicated this algorithm achieved higher re-identification rate for re-identification, and more robust to viewing condition changes, illumination variations, background clutter and occlusion. |
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