Multi-view implicit transfer for person re-identification
Wei Xu, Yijun Li, Chen Gong, Jie Yang
Abstract
Implicit camera transfer (ICT), which models the multi-valued mappings between two specific and stationary cameras, is a descent solution for the person re-identification problem of the surveillance system. It has the properties of simplicity, computational efficiency and well utilizing negative training data. But it neglects the complementary relation between the descriptors of various views. And different appearance people have various most discriminative views among all the views, which are under diverse mappings. To tackle with this constraint, we model the multi-values mapping from different view independently, and fuse these transferring results of each view by LPBoost. Experimental results demonstrate that our scheme not only inherits most of the advantages (some sacrifice in speed, but still can run in real time for the same testing case in the ICT paper) of ICT but also obtains more discriminative mappings than ICT. In addition, our solution gains competitive performance on 2 challenging datasets.
BibTeX
@inproceedings{icassp2015_multiviewimplici,
title = {Multi-view implicit transfer for person re-identification},
author = {Wei Xu and Yijun Li and Chen Gong and Jie Yang},
booktitle = {ICASSP 2015},
year = {2015}
}