Attention-guided cross-modality person re-identification

Yulin Liu

doi:10.1117/12.2647477

7 September 2022 Attention-guided cross-modality person re-identification

Yulin Liu

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 1232905 (2022) https://doi.org/10.1117/12.2647477
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

Cross-modality person re-identification, also known as RGB-infrared person re-identification, is a person recognition and retrieval technology between visible and infrared images. As an essential technologies of video intelligent surveillance system, the technology is urgently needed in security monitoring and suspect tracking. The modality discrepancy and intra-class variations in cross-modality person re-identification make it difficult to extract effective discriminable features of person identity. There are significantly fewer effective discriminable features in the shared feature space caused by shared network parameters. In order to solve this problem, an attention-guided cross-modality person re-identification is designed in this paper. The attention module uses the attention mechanism to focus on the salient features, so as to guide the network to put more parameters on the learning of salient features, so that the network can learn more discriminable, features from salient features. A comparative experiment on two standard data sets of cross-modality person re-identification verifies the effectiveness and advancement of the proposed method. For example, the proposed method improves rank-1 by 17.79% on SYSU-MM01 and 16.55% on mAP.

Citation Download Citation

Yulin Liu "Attention-guided cross-modality person re-identification", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 1232905 (7 September 2022); https://doi.org/10.1117/12.2647477

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available