Person re-identification by multi-channel feature cascading

• Published in: 5th IET International Conference on Wireless, Mobile and Multimedia Networks (ICWMMN 2013) p. 4.03
• Main Authors: Mingyong Zeng, Chang Tian, Zemin Wu, Yi Fu, Feiran Jie
• Format: Conference Proceeding
• Language: English
• Published: Stevenage, UK IET 2013; The Institution of Engineering & Technology
• Subjects: Computer vision and image processing techniques; Image recognition; public gallery VIPeR; person re-identification problem; ensemble of localized features method; ELF method; image colour analysis; multichannel cascading feature; image recognition
• ISBN: 9781849197267; 1849197261
• DOI: 10.1049/cp.2013.2408

Person re-identification is a non-trivial problem due to many challenging factors such as different views or varying illumination. The person re-identification problem is discussed in views of feature cascading and combining in this paper. After a detailed analysis of the disadvantages of the ELF (Ensemble of Localized Features) method, features by cascading multiple channels at proper regions are investigated on the reidentification performance. In the proposed exploring framework, it's found that the cascading histogram feature with YCbCrHS channels within interior regions can achieve excellent performance. The proposed excellent multi-channel cascading feature (MCCF) is then combined with other features for further improvement. Extensive validation and comparative experiments were conducted on the public gallery VIPeR. And the experimental results show that the proposed feature MCCF and the combined feature can achieve comparable or better performance on person re-identification than other state-of-the- art features.