关键词: 行人重识别, 计算机视觉, 基于视频, 质量评估, 属性识别, 对齐

Abstract:

To solve the difficulties brought by illumination and viewpoint varieties in video-based person re-identification（re-ID）, a network combining the region-based quality estimation and attribute classification is proposed. Some images are pre-processed by cutting the bottom part. the images are input into convolutional network after being divided into three-part-division, which will predict the quality of each part. the network is trained by combining with the attribute labels of pedestrians to finish the whole re-ID process. Through learning global features and local features of pedestrians, the network can effectively handle occlusions and misalignments, thus achieve comparable results in three public datasets.

Key words: person re-identification, computer vision, video-based, quality estimation, attribute classification, alignment