DocumentCode :
3707307
Title :
Ellipse-specific fitting by relaxing the 3L constraints with semidefinite programming
Author :
Jiangpeng Rong;Sen Yang;Xiang Mei;Xianghua Ying;Shiyao Huang;Hongbin Zha
Author_Institution :
Key Laboratory of Machine Perception (Ministry of Education), School of Electronic Engineering and Computer Science, Center for Information Science, Peking University, Beijing 100871, P.R. China
fYear :
2015
Firstpage :
710
Lastpage :
714
Abstract :
This paper presents a new efficient method to increase the accuracy and the robustness of ellipse fitting, by utilizing the 3L algorithm and semidefinite programming (SDP). The novelty lies on the combination of relaxed geometric distance constraints and semidefinite programming framework. Due to the relaxed 3L constraints, the proposed approach provides high robustness in the presence of noise. The accuracy of the final solution is prominently increased even if the data suffer from strong occlusions or noises. The proposed method represents significant advantages in both accuracy and robustness. Experimental results and comparisons with state-of-the-art fitting methods demonstrate the improvements in ellipse fitting.
Keywords :
"Fitting","Robustness","Convex functions","Noise level","Polynomials","Level set","Shape"
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/ICIP.2015.7350891
Filename :
7350891
Link To Document :
بازگشت