Progressive Domain Adaptation for Robot Vision Person Re-identification

被引：4

作者：

Sha, Zijun ^{[1
]}

Zeng, Zelong ^{[2
]}

Wang, Zheng ^{[3
]}

Natori, Yoichi ^{[1
]}

Taniguchi, Yasuhiro ^{[1
]}

Satoh, Shin'ichi ^{[3
]}

机构：

[1] Honda Res & Dev Co Ltd, Wako, Saitama, Japan

[2] Univ Tokyo, Tokyo, Japan

[3] Natl Inst Informat, Tokyo, Japan

来源：

MM '20: PROCEEDINGS OF THE 28TH ACM INTERNATIONAL CONFERENCE ON MULTIMEDIA | 2020年

关键词：

Robot Vision; Domain Adaptation; Person Re-identification;

D O I：

10.1145/3394171.3414358

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Person re-identification has received much attention in the last few years, as it enhances the retrieval effectiveness in the video surveillance networks and video archive management. In this paper, we demonstrate a guiding robot with person followers system, which recognizes the follower using a person re-identification technology. It first adopts existing face recognition and person tracking methods to generate person tracklets with different IDs. Then, a classic person re-identification model, pre-trained on the surveillance dataset, is adapted to the new robot vision condition incrementally. The demonstration showcases the quality of robot follower focusing.

引用

页码：4488 / 4490

页数：3

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