标题:A G2G Similarity Guided Pedestrian Re-identification Algorithm    (Open Access)
作者:Wang, Guangcai ;Gao, Shang ;Fan, Di
通讯作者:Fan, Di
作者机构:[Wang, Guangcai ;Gao, Shang ;Fan, Di ] College of Electronic Information Engineering, Shandong University of Science and Technology, Qingdao, Shandong 更多
会议名称:2019 2nd International Conference on Computer Information Science and Artificial Intelligence, CISAI 2019
会议日期:October 25, 2019 - October 27, 2019
来源:Journal of Physics: Conference Series
出版年:2020
卷:1453
期:1
DOI:10.1088/1742-6596/1453/1/012035
摘要:Pedestrian re-identification aims to settle the matching problem for a given target pedestrian under the multi-camera with non-overlapping visual field, so as to achieve the goal of pedestrian retrieval. In this paper, the similarity between the gallery images (G2G similarity) will be used to guide and refine the similarity between query images and gallery images (P2G similarity). It is also introduced into the training process and playing a supervisory role. To fully utilize details of the images, the image features are horizontally overlapped into groups, and the similarities between each group of the query images and the gallery images are calculated respectively. By learning the weights of grouping features in the training process, the importance of key parts can be automatically perceived. The results on the Market-1501 and CUHK03 datasets prove the effectiveness of proposed algorithm.
© Published under licence by IOP Publishing Ltd.
收录类别:EI
资源类型:会议论文
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