Title
Robust Fusion of Color and Depth Data for RGB-D Target Tracking Using Adaptive Range-Invariant Depth Models and Spatio-Temporal Consistency Constraints.
Abstract
This paper presents a novel robust method for single target tracking in RGB-D images, and also contributes a substantial new benchmark dataset for evaluating RGB-D trackers. While a target object's color distribution is reasonably motion-invariant, this is not true for the target's depth distribution, which continually varies as the target moves relative to the camera. It is therefore nontrivial t...
Year
DOI
Venue
2018
10.1109/TCYB.2017.2740952
IEEE Transactions on Cybernetics
Keywords
Field
DocType
Target tracking,Benchmark testing,Robustness,Adaptation models,Videos,Image color analysis
BitTorrent tracker,Computer vision,Fusion,Exploit,Robustness (computer science),Video tracking,Artificial intelligence,Invariant (mathematics),RGB color model,Mathematics,Benchmark (computing)
Journal
Volume
Issue
ISSN
48
8
2168-2267
Citations 
PageRank 
References 
4
0.40
0
Authors
4
Name
Order
Citations
PageRank
Jingjing Xiao1444.10
Rustam Stolkin252739.74
Yuqing Gao348053.03
Ales Leonardis4383.43