Name
Title | ||
|---|---|---|
Non-negative Dual Graph Regularized Sparse Ranking for Multi-shot Person Re-identification. |
Abstract | ||
|---|---|---|
Person re-identification (Re-ID) has recently attracted enthusiastic attention due to its potential applications in social security and smart city surveillance. The promising achievement of sparse coding in image based recognition gives rise to a number of development on Re-ID especially with limited samples. However, most of existing sparse ranking based Re-ID methods lack of considering the geometric structure on the data. In this paper, we design a non-negative dual graph regularized sparse ranking method for multi-shot person Re-ID. First, we enforce a global graph regularizer into the sparse ranking model to encourage the probe images from the same person generating similar coefficients. Second, we enforce additional local graph regularizer to encourage the gallery images of the same person making similar contributions to the reconstruction. At last, we impose the non-negative constraint to ensure the meaningful interpretation of the coefficients. Based on these three cues, we design a unified sparse ranking framework for multi-shot Re-ID, which aims to simultaneously capture the meaningful geometric structures within both probe and gallery images. Finally, we provide an iterative optimization algorithm by Accelerated Proximal Gradient (APG) to learn the reconstruction coefficients. The ranking results of a certain probe against given gallery are obtained by accumulating the re-distributed reconstruction coefficients. Extensive experiments on three benchmark datasets, i-LIDS, CAVIARA4REID and MARS with both hand-crafted and deep features yield impressive performance in multi-shot Re-ID. |
Year | Venue | Field |
|---|---|---|
2018 | PRCV | Data mining,Graph,Ranking,Neural coding,Computer science,Image based,Dual graph,Optimization algorithm,Smart city |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
22 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aihua Zheng | 1 | 36 | 12.40 |
| Hongchao Li | 2 | 23 | 4.20 |
| Bo Jiang | 3 | 119 | 17.21 |
| Chenglong Li | 4 | 282 | 34.38 |
| Jin Tang | 5 | 322 | 62.02 |
| Bin Luo | 6 | 802 | 107.57 |