Clothing Attributes Assisted Person Reidentification
Clothing Attributes Assisted Person Reidentification
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DOI：
10.1109/tcsvt.2014.2352552
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发表时间：
2015-05
影响因子：
8.4
通讯作者：
Annan Li;Luoqi Liu;Kang Wang;Si Liu;Shuicheng Yan
中科院分区：
文献类型：
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作者：
Annan Li;Luoqi Liu;Kang Wang;Si Liu;Shuicheng Yan
在不重叠的摄像机视图中重新识别人是一项相当具有挑战性的任务。由于难以获得可识别的面孔，服装外观成为识别目的的主要线索。在本文中，我们提出了一个全面的研究服装属性辅助人的再识别。首先，提取身体部位及其局部特征，以缓解姿势不对准问题。提出了一种基于LSVM的人物再识别方法，该方法描述了人物对的底层部件特征、中层服装属性和高层再识别标签之间的关系。由于服装属性的不确定性，我们将其视为实值变量，而不是将其作为离散变量。此外，本文还收集了包含10个相机视图和约200个主题的大规模真实世界数据集并进行了全面注释。在此数据集上的大量实验表明：1）部分特征比从整体人体边界框中提取的特征更有效; 2）与不含服装属性的支持向量机相比，嵌入LSVM模型中的服装属性可以进一步提高重新识别性能; 3）将服装属性作为实值变量处理比将其作为离散变量处理更有效。
Person reidentification across nonoverlapping camera views is a rather challenging task. Due to the difficulties in obtaining identifiable faces, clothing appearance becomes the main cue for identification purposes. In this paper, we present a comprehensive study on clothing attributes assisted person reidentification. First, the body parts and their local features are extracted for alleviating the pose-misalignment issue. A latent support vector machine (LSVM)-based person reidentification approach is proposed to describe the relations among the low-level part features, middle-level clothing attributes, and high-level reidentification labels of person pairs. Motivated by the uncertainties of clothing attributes, we treat them as real-value variables instead of using them as discrete variables. Moreover, a large-scale real-world dataset with 10 camera views and about 200 subjects is collected and thoroughly annotated for this paper. The extensive experiments on this dataset show: 1) part features are more effective than features extracted from the holistic human bounding boxes; 2) the clothing attributes embedded in the LSVM model may further boost reidentification performance compared with support vector machine without clothing attributes; and 3) treating clothing attributes as real-value variables is more effective than using them as discrete variables in person reidentification.