Name
Title | ||
|---|---|---|
Person re-identification based on gait via Part View Transformation Model under variable covariate conditions |
Abstract | ||
|---|---|---|
Human gait represents an attractive biometric modality to re-identify a person as it requires non contact and it is perceivable at a distance. However, the view angle variation and the presence of covariate factors cause significant difficulties for recognizing gaits. In order to deal with such constraints, this paper presents a Part View Transformation Model (PVTM) for gait based applications. Compared with previous methods, the PVTM is applied on selected relevant parts chosen through a semantic classification step. Conducted on the CASIA-B gait database, experimental results show that the proposed method outperforms well known multi-view methods even under covariate factors (i.e. carrying bag, clothing). |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.jvcir.2021.103093 | Journal of Visual Communication and Image Representation |
Keywords | DocType | Volume |
Re-identification,Gait,Part View Transformation Model (PVTM),View angle variation,Covariate factors | Journal | 77 |
ISSN | Citations | PageRank |
1047-3203 | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Imen Chtourou | 1 | 2 | 1.38 |
| Emna Fendri | 2 | 12 | 7.28 |
| Mohamed Hammami | 3 | 181 | 30.54 |