Task-specific neural networks for pose estimation in person re-identification task

Kai Lv, Hao Sheng, Yanwei Zheng, Zhang Xiong, Wei Li, Wei Ke

研究成果: Conference contribution同行評審

摘要

Person re-identification is a challenging task because of severe appearance changes of a person due to diverse camera viewpoints and person poses. To alleviate the impact of different poses, more and more studies have been done in pose estimation. In this work, we present three task-specific neural networks (TNN) algorithm designed to address the problem of pose estimation for re-identification in both single-shot and multi-shot matching. In order to recognize the human pose as one of the four classes (front, back, left, right), a PoseNet-A is first required to estimate the pose as class front-back or class left-right. Based on the results, we select the appropriate network (PoseNet-B1, PoseNet-B2) to obtain the final pose. According to the results, our method achieves very good results on a large data set (CUHK03-Pose). One thing that needs to be pointed out is that we build the dataset CUHK03-Pose which is based on the person re-identification dataset CUHK03.

原文English
主出版物標題Advances in Multimedia Information Processing – PCM 2017 - 18th Pacific-Rim Conference on Multimedia, Revised Selected Papers
編輯Bing Zeng, Hongliang Li, Abdulmotaleb El Saddik, Xiaopeng Fan, Shuqiang Jiang, Qingming Huang
發行者Springer Verlag
頁面792-801
頁數10
ISBN(列印)9783319773797
DOIs
出版狀態Published - 2018
事件18th Pacific-Rim Conference on Multimedia, PCM 2017 - Harbin, China
持續時間: 28 9月 201729 9月 2017

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10735 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

Conference

Conference18th Pacific-Rim Conference on Multimedia, PCM 2017
國家/地區China
城市Harbin
期間28/09/1729/09/17

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