Salient Color Names for Person Re-identification
Salient Color Names for Person Re-identification
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DOI：
10.1007/978-3-319-10590-1_35
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发表时间：
2014-09
期刊：
影响因子：
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通讯作者：
Yang Yang-Yang;Jimei Yang;Junjie Yan;Shengcai Liao;Dong Yi;S. Li
中科院分区：
文献类型：
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作者：
Yang Yang-Yang;Jimei Yang;Junjie Yan;Shengcai Liao;Dong Yi;S. Li
在许多计算机视觉应用中，将颜色与颜色名称联系起来的颜色命名可以帮助人们对图像进行语义分析。本文提出了一种新的基于显著颜色名称的颜色描述符（SCNCD）来描述颜色。SCNCD使用显著的颜色名称来保证更接近颜色的颜色名称被分配的概率更高。基于SCNCD，获得不同颜色空间中颜色名称的颜色分布，并进行融合生成特征表示。并分析了背景信息对人物再识别的影响。通过简单的度量学习方法，所提出的方法在两个具有挑战性的数据集（VIPeR和PRID 450S）上优于最先进的性能（没有用户反馈优化）。更重要的是，如果我们提前计算每种颜色的SCNCD，可以非常快速地获得所提出的特征。
Color naming, which relates colors with color names, can help people with a semantic analysis of images in many computer vision applications. In this paper, we propose a novel salient color names based color descriptor (SCNCD) to describe colors. SCNCD utilizes salient color names to guarantee that a higher probability will be assigned to the color name which is nearer to the color. Based on SCNCD, color distributions over color names in different color spaces are then obtained and fused to generate a feature representation. Moreover, the effect of background information is employed and analyzed for person re-identification. With a simple metric learning method, the proposed approach outperforms the state-of-the-art performance (without user’s feedback optimization) on two challenging datasets (VIPeR and PRID 450S). More importantly, the proposed feature can be obtained very fast if we compute SCNCD of each color in advance.