NDLI: Deep part-related feature learning for human-level biometrics

Content Provider	IET Digital Library
Author	Zhou, Zhiheng Chen, Zengqun Huang, Junchu Zhang, Yusheng
Abstract	Many human-level biometrics systems rely on visual appearance to solve re-identification problems. Most of them focus on recognizing local visual regions individually, without exploiting the relations between these separated visual regions during learning. In this study, the authors target on learning discriminative part-related features and present novel network architecture, part relation network (PRN). It processes a set of part objects simultaneously in an end-to-end way to model relations of their appearance features, which strengthens the discriminative ability of local representation. Specially, the authors design PRN as a two-branch deep network, each branch of which performs uniform partition with different numbers of stripes to obtain multi-scale and cross-over part features for identification. Experimental results demonstrate that this system achieves state-of-the-art performance on three challenging data sets including Market-1501, CUHK03, and DukeMTMC-reID and demonstrate the effectiveness of modelling part relations for biometrics.
Starting Page	332
Ending Page	339
Page Count	8
ISSN	20474938
Volume Number	8
e-ISSN	20474946
Issue Number	Issue 5, Sep (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/8/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2018.5227
Journal	IET Biometrics
Publisher Date	2019-04-26
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Appearance Features Biomimetics Computer Vision And Image Processing Technique Deep Part-related Feature Learning Discriminative Ability Feature Extraction Human-level Biometrics System Image Recognition Image Representation Knowledge Engineering Technique Learning Discriminative Part-related Feature Learning in AI Local Representation Local Visual Region Novel Network Architecture Part Relation Network PRN Re-identification Problem Separated Visual Region Two-branch Deep Network Visual Appearance
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

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