Name
Title | ||
|---|---|---|
Information fusion from multiple cameras for gait-based re-identification and recognition |
Abstract | ||
|---|---|---|
In this study, the authors present a fully automated frontal (i.e. employing front and back views only) gait recognition approach using the depth information captured by multiple Kinect RGB-D cameras. Limited depth sensing range restricts each of these Kinects to record only a part of a complete gait cycle of a walking subject. Hence, information from more than one Kinect is fused together to examine which features of a gait cycle can be conveniently extracted from the sequences captured independently by these cameras. To achieve this, it is imperative that the same subject be re-identified as he moves from the field of view of one camera to another. The authors use a set of soft-biometric features computed from the skeleton stream provided by Kinect software development kit) for doing automatic re-identification. To enable such information fusion and also to handle missing components even after re-identification, features are extracted at the granularity of small fractions of a gait cycle. Experiments carried out on a data set with gait videos captured by Kinects respectively from the back and front views show promising results. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1049/iet-ipr.2014.0773 | Image Processing, IET |
Keywords | DocType | Volume |
feature extraction,image recognition,image sensors,medical image processing,sensor fusion,Kinect software development kit,feature extraction,gait recognition approach,gait-based re-identification,information fusion,multiple cameras,multiple kinect RGB-D cameras | Journal | 9 |
Issue | ISSN | Citations |
11 | 1751-9659 | 2 |
PageRank | References | Authors |
0.36 | 8 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pratik Chattopadhyay | 1 | 52 | 6.81 |
| Shamik Sural | 2 | 1008 | 96.36 |
| Jayanta Mukherjee | 3 | 378 | 56.06 |