DocumentCode
2003197
Title
A New Algorithm for Target Recognition and Tracking for Robot Vision System
Author
Xia, Guihua ; Xing, Zhuoyi
Author_Institution
Harbin Eng. Univ., Harbin
fYear
2007
fDate
May 30 2007-June 1 2007
Firstpage
1004
Lastpage
1008
Abstract
Target recognition and tracking is the key destination in robot vision system. A new efficient algorithm is introduced in this paper to overcome the contradiction among the complexity of algorithm, tracking precision, and the rapidity in real-time system. Firstly, the algorithm is based on the feature of template cursory matching by lowering resolution and using sequential similarity detection algorithm (SSDA) with four items of improvement to locate the position. Secondly, it brings forward a template update algorithm based on confidence level maximum close distance, as the target varying posture and moving constantly. Finally, Kalman filter algorithm is used to estimate the position and it can reduce the ratio of losing target when the target is sheltered. The experiments and simulations show that the algorithms given in the paper have advantages of improving orientation precision, rapidity, practicability, and robustness in orientating target.
Keywords
Kalman filters; image matching; position control; robot vision; target tracking; Kalman filter; confidence level maximum close distance; position estimation; robot vision system; sequential similarity detection algorithm; target recognition; template cursory matching; template update algorithm; tracking; Artificial intelligence; Automatic control; Digital images; Image recognition; Image segmentation; Intelligent robots; Robot vision systems; Robotics and automation; Target recognition; Target tracking; Confidence level; Feature of template; Kalman filter; Robot vision;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Automation, 2007. ICCA 2007. IEEE International Conference on
Conference_Location
Guangzhou
Print_ISBN
978-1-4244-0817-7
Electronic_ISBN
978-1-4244-0818-4
Type
conf
DOI
10.1109/ICCA.2007.4376507
Filename
4376507
Link To Document