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