Orientation Driven Bag of Appearances for Person Re-identification
Liqian Ma, Hong Liu, Liang Hu, Can Wang, Qianru Sun

TL;DR
This paper introduces a novel person re-identification method that leverages body structure and orientation information to improve feature representation and matching accuracy across camera views.
Contribution
It proposes the Body-Structure Based Feature Representation (BSFR) and Orientation Driven Bag of Appearances (ODBoA), incorporating body structure and orientation cues for enhanced re-identification.
Findings
Outperforms existing methods on multiple datasets
Effectively handles pose and viewpoint variations
Demonstrates the benefit of body structure and orientation info
Abstract
Person re-identification (re-id) consists of associating individual across camera network, which is valuable for intelligent video surveillance and has drawn wide attention. Although person re-identification research is making progress, it still faces some challenges such as varying poses, illumination and viewpoints. For feature representation in re-identification, existing works usually use low-level descriptors which do not take full advantage of body structure information, resulting in low representation ability. %discrimination. To solve this problem, this paper proposes the mid-level body-structure based feature representation (BSFR) which introduces body structure pyramid for codebook learning and feature pooling in the vertical direction of human body. Besides, varying viewpoints in the horizontal direction of human body usually causes the data missing problem, , the…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVideo Surveillance and Tracking Methods · Face recognition and analysis · Advanced Image and Video Retrieval Techniques
