Paper Info
Title
Combined Motion and Region-Based 3D Tracking in Active Depth Image Sequence
Abstract
Robustness needs to be specially emphasised in visual tracking based on active depth camera, due to its high-level noise and limited accuracy. In this paper, we present a robust 3D tracking approach that is able to extract object-independent motion trajectory under uncontrolled environment. Two novel algorithms are designed, including a motion-based tracking approach and a region-based approach, then a Kalman filter is employed to fuse their tracking results. This method is low-level and object-independent, we test its performance in tracking moving people and gesture. Experimental results shows that this method can tackle the situation of entry, exit, high noise, complex background, complex motion, and non-rigid motion.
Year
DOI
Venue
2013
10.1109/GreenCom-iThings-CPSCom.2013.319
GreenCom/iThings/CPScom
Keywords
Field
DocType
gesture tracking,kalman filter,visual tracking,kalman filters,image fusion,complex motion,object-independent motion trajectory,motion-based tracking approach,region-based approach,active depth camera,non-rigid motion,active depth image,depth image,complex background,combined motion,object tracking,motion-based 3d tracking approach,image sequences,tracking result,hand tracking,robust 3d tracking approach,active depth image sequence,high noise,high-level noise,moving people tracking,region-based 3d tracking approach,activity monitoring,image motion analysis
Computer vision,Image fusion,Computer science,Finger tracking,Tracking system,Kalman filter,Robustness (computer science),Eye tracking,Video tracking,Artificial intelligence,Trajectory
Conference
Citations 
PageRank 
References 
0
0.34
6
Authors
4
Name
Order
Citations
PageRank
Xingyu Wu1152.28
Xia Mao218821.89
Lijiang Chen330423.22
Angelo Compare4293.81