DocumentCode
2225856
Title
Minimum description length Shape Model based on bio-inspired features
Author
Wang, Shaoyu ; Huang, Yongfeng ; Qin, Zhidong ; Liao, Xiaoyong ; Luo, Youjun
Author_Institution
Sch. of Comput. Sci. & Technol., Donghua Univ., Shanghai, China
Volume
5
fYear
2010
fDate
20-22 Aug. 2010
Abstract
This paper proposes an enhanced MDL Shape Model to solve the point correspondence problem. The current MDL methods build models mainly based on shape information and may get bad models. Motivated by the biologically inspired features (BIF), which inspired by visual cortex, we compute the C1 response on the master node and add the cost of BIF across training set to the objective function of MDL Shape Models. Experiments show that our method can get better model and point correspondence.
Keywords
feature extraction; shape recognition; statistical analysis; MDL shape model; bio-inspired features; master node; minimum description length shape model; point correspondence problem; shape information; visual cortex; Biological system modeling; Manuals; Shape; MDL shape model; biologically inspired features; gabor filters; statistical shape models; visual cortex;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
Conference_Location
Chengdu
ISSN
2154-7491
Print_ISBN
978-1-4244-6539-2
Type
conf
DOI
10.1109/ICACTE.2010.5579439
Filename
5579439
Link To Document