Person re-identification by Local Maximal Occurrence representation and metric learning
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这是中科院关于Person re-identification CVPR 2015
- Local Maximal Occurrence Feature
3.1. Dealing with Illumination Variations
首先对图像使用 Retinex 进行了预处理,前后结果如下图所示:
对处理后的图像,我们通过计算 HSV color histogram 来提取颜色特征。
In addition to color description, we also apply the Scale Invariant Local Ternary Pattern (SILTP) [26] descriptor for illumination invariant texture description
3.2. Dealing with Viewpoint Changes
4.Cross-view Quadratic Discriminant Analysis
4.1. Bayesian Face and KISSME Revisit
这里简单介绍了一下我们参考的两个方法,Bayesian Face and KISSME
4.2. XQDA
这里我们提出了自己的方法,经过公式推导,最后的优化公式为:
5 Experiments
1 0
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- Person Re-identification Datasets
- Person Re-identification Datasets
- Person Re-identification Overview
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