DocumentCode
2399891
Title
Local tensor descriptor from micro-deformation analysis
Author
Cheng, Bangsheng
Author_Institution
Biomed. Eng. Dept., Zhejiang Univ., Hangzhou
fYear
2008
fDate
23-28 June 2008
Firstpage
1
Lastpage
8
Abstract
This paper proposes a novel method called micro-deformation analysis to analyze and describe local image structures. This method is a general analytic tool and can be applied to any high-dimensional scalar or vector functions. We derive the tensor matrix from this method as the descriptor to represent the information within local image patches. Our experimental results suggest that we can design low-dimensional local tensor descriptors with performance comparable to the popular SIFT descriptor, which is the state-of-the-art feature descriptor used for object recognition and categorization.
Keywords
matrix algebra; object recognition; feature descriptor; local image structures; local tensor descriptor; microdeformation analysis; object categorization; object recognition; tensor matrix; Biomedical engineering; Computer vision; Deformable models; Filter bank; Gabor filters; Histograms; Image analysis; Object recognition; Physics; Tensile stress;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on
Conference_Location
Anchorage, AK
ISSN
1063-6919
Print_ISBN
978-1-4244-2242-5
Electronic_ISBN
1063-6919
Type
conf
DOI
10.1109/CVPR.2008.4587610
Filename
4587610
Link To Document