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 :
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