Paper Info
Title
Real-Time Visual Target Tracking in RGB-D Data for Person-Following Robots
Abstract
This paper describes a novel RGB-D-based visual target tracking method for person-following robots. We enhance a single-object tracker, which combines RGB and depth information, by exploiting two different types of distracters. First set of distracters includes objects existing near-by the target, and the other set is for objects looking similar to the target. The proposed algorithm reduces tracking drifts and wrong target re-identification by exploiting the distracters. Experiments on real-world video sequences demonstrating a person-following problem show a significant improvement over the method without tracking distracters and state-of-the-art RGB-based trackers. A mobile robot following a person is tested in real environment.
Year
DOI
Venue
2014
10.1109/ICPR.2014.387
ICPR
Keywords
Field
DocType
person-following problem,real-time visual target tracking,visual tracking, person tracking, rgb-d camera, mobile robots,video signal processing,visual tracking,person-following robots,tracking drift,rgb-d camera,target reidentification,target tracking,person tracking,mobile robots,object tracking,image sequences,rgb-d-based visual target tracking method,depth information,real-world video sequences,mobile robot,rgb-d data,rgb-based tracker,single-object tracker,robot vision,image colour analysis
Computer vision,Computer graphics (images),Computer science,Tracking system,Video tracking,Artificial intelligence,RGB color model,Visual target tracking,Robot
Conference
ISSN
Citations 
PageRank 
1051-4651
1
0.35
References 
Authors
0
4
Name
Order
Citations
PageRank
Youngwoo Yoon1236.15
Woo-han Yun2236.06
Ho-Sub Yoon3113.88
Jaehong Kim438341.59