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Person Re-identification by Salience Matching

Published: 01 December 2013 Publication History

Abstract

Human salience is distinctive and reliable information in matching pedestrians across disjoint camera views. In this paper, we exploit the pair wise salience distribution relationship between pedestrian images, and solve the person re-identification problem by proposing a salience matching strategy. To handle the misalignment problem in pedestrian images, patch matching is adopted and patch salience is estimated. Matching patches with inconsistent salience brings penalty. Images of the same person are recognized by minimizing the salience matching cost. Furthermore, our salience matching is tightly integrated with patch matching in a unified structural Rank SVM learning framework. The effectiveness of our approach is validated on the VIPeR dataset and the CUHK Campus dataset. It outperforms the state-of-the-art methods on both datasets.

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Published In

cover image Guide Proceedings
ICCV '13: Proceedings of the 2013 IEEE International Conference on Computer Vision
December 2013
3650 pages
ISBN:9781479928408

Publisher

IEEE Computer Society

United States

Publication History

Published: 01 December 2013

Author Tags

  1. Person re-identification
  2. patch matching
  3. pedestrian matching
  4. salience
  5. salience matching
  6. saliency

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  • (2023)Neural Architectures for Feature Embedding in Person Re-Identification: A Comparative ViewACM Transactions on Intelligent Systems and Technology10.1145/361029814:5(1-21)Online publication date: 9-Oct-2023
  • (2022)SiSL-NetNeurocomputing10.1016/j.neucom.2022.09.029510:C(193-202)Online publication date: 21-Oct-2022
  • (2020)Cross Modal Person Re-identification with Visual-Textual Queries2020 IEEE International Joint Conference on Biometrics (IJCB)10.1109/IJCB48548.2020.9304940(1-8)Online publication date: 28-Sep-2020
  • (2019)Binarized neural networks for resource-efficient hashing with minimizing quantization lossProceedings of the 28th International Joint Conference on Artificial Intelligence10.5555/3367032.3367179(1032-1040)Online publication date: 10-Aug-2019
  • (2019)Multi-shot Person Re-identification through Set Distance with Visual Distributional RepresentationProceedings of the 2019 on International Conference on Multimedia Retrieval10.1145/3323873.3325030(262-270)Online publication date: 5-Jun-2019
  • (2019)Multi-level Similarity Perception Network for Person Re-identificationACM Transactions on Multimedia Computing, Communications, and Applications10.1145/330988115:2(1-19)Online publication date: 5-Jun-2019
  • (2019)On Low-Resolution Face Recognition in the WildIEEE Transactions on Information Forensics and Security10.1109/TIFS.2018.289081214:8(2000-2012)Online publication date: 1-Aug-2019
  • (2019)From person to group re-identification via unsupervised transfer of sparse featuresImage and Vision Computing10.1016/j.imavis.2019.02.00983:C(29-38)Online publication date: 1-Mar-2019
  • (2019)Body Part-Based Person Re-identification Integrating Semantic AttributesNeural Processing Letters10.1007/s11063-018-9887-449:3(1111-1124)Online publication date: 1-Jun-2019
  • (2019)People tracking in multi-camera systemsMultimedia Tools and Applications10.1007/s11042-018-6638-578:8(10773-10793)Online publication date: 1-Apr-2019
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