Title :
Fusion of laser and vision for multiple targets tracking via on-line learning
Author :
Song, Xuan ; Zhao, Huijing ; Cui, Jinshi ; Shao, Xiaowei ; Shibasaki, Ryosuke ; Zha, Hongbin
Abstract :
Multi-target tracking becomes significantly more challenging when the targets are in close proximity or frequently interact with each other. This paper presents a promising tracking system to deal with these problems. The novelty of this system is that laser and vision, tracking and learning are integrated and can complement each other in one framework: when the targets do not interact with each other, the laser-based independent trackers are employed and the visual information is extracted simultaneously to train some classifiers for the “possible interacting targets”. When the targets are in close proximity, the learned classifiers and visual information are used to assist in tracking. Therefore, this mode of co-operation between them not only deals with various tough problems encountered in the tracking, but also ensures that the entire process can be completely on-line and automatic. Experimental results demonstrated that laser and vision fully display their respective advantages in our system, and it is easy for us to obtain a perfect trade-off between tracking accuracy and time-cost.
Keywords :
computer vision; target tracking; laser fusion; laser-based independent trackers; multiple targets tracking; online learning; vision fusion; visual information extraction; Cameras; Educational technology; Geometry; Image segmentation; Intelligent robots; Laser fusion; Layout; Pattern matching; Photometry; Target tracking;
Conference_Titel :
Robotics and Automation (ICRA), 2010 IEEE International Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
978-1-4244-5038-1
Electronic_ISBN :
1050-4729
DOI :
10.1109/ROBOT.2010.5509486