Volume-based human re-identification with RGB-D cameras

Cosar, Serhan and Coppola, Claudio and Bellotto, Nicola (2017) Volume-based human re-identification with RGB-D cameras. In: VISAPP - International Conference on Computer Vision Theory and Applications, 27 Feb - 1 Mar 2017, Porto, Portugal.

Full text not available from this repository.

Item Type:Conference or Workshop contribution (Presentation)
Item Status:Live Archive

Abstract

This paper presents an RGB-D based human re-identification approach using novel biometrics features from the body's volume. Existing work based on RGB images or skeleton features have some limitations for real-world robotic applications, most notably in dealing with occlusions and orientation of the user. Here, we propose novel features that allow performing re-identification when the person is facing side/backward or the person is partially occluded. The proposed approach has been tested for various scenarios including different views, occlusion and the public BIWI RGBD-ID dataset.

Keywords:re-identification, volume-based features, occlusion, body motion, service robots
Subjects:G Mathematical and Computer Sciences > G700 Artificial Intelligence
H Engineering > H671 Robotics
G Mathematical and Computer Sciences > G740 Computer Vision
Divisions:College of Science > School of Computer Science
ID Code:25360
Deposited On:15 Dec 2016 20:30

Repository Staff Only: item control page