Title :
Research of tracking robot based on SURF features
Author :
Bing, Zhigang ; Wang, Yongxia ; Hou, Jinsheng ; Lu, Hailong ; Chen, Hongda
Author_Institution :
Tianjin Univ. of Technol. & Educ., Tianjin, China
Abstract :
A tracking algorithm using Kalman Filter (KF) based on Speed-up Robust Features (SURF) is proposed. In the tracking process, the SURF features in the frames are matched by RANdom SAmple Consensus (RANSAC) with objective template, and the Fuzzy C-Means (FCM) clustering analysis is used to eliminate the mismatching cases. Then the precise position of the object is determined, and the KF prediction of the object position is calibrated. The experiment results verify the robustness and real-time of the proposed method.
Keywords :
Kalman filters; mobile robots; pattern clustering; robot vision; target tracking; Kalman filter; RANSAC; SURF features; fuzzy C-means clustering analysis; object position; random sample consensus; speed-up robust features; tracking robot; Feature extraction; Real time systems; Robot sensing systems; Robustness; Target tracking; FCM Clustering; KF; Object tracking; RANSAC; Robot; SURF;
Conference_Titel :
Natural Computation (ICNC), 2010 Sixth International Conference on
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-1-4244-5958-2
DOI :
10.1109/ICNC.2010.5584230
