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» Highly Discriminative Invariant FEatures for Image Matching
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ICCV
2009
IEEE
1821views Computer Vision» more  ICCV 2009»
16 years 6 months ago
Feature Correspondence and Deformable Object Matching via Agglomerative Correspondence Clustering
We present an efficient method for feature correspondence and object-based image matching, which exploits both photometric similarity and pairwise geometric consistency from local ...
Minsu Cho (Seoul National University), Jungmin Lee...
CVPR
2006
IEEE
16 years 4 months ago
Local Features, All Grown Up
We present a technique to adapt the domain of local features through the matching process to augment their discriminative power. We start with local affine features selected and n...
Andrea Vedaldi, Stefano Soatto
PAMI
2007
157views more  PAMI 2007»
15 years 1 months ago
Pores and Ridges: High-Resolution Fingerprint Matching Using Level 3 Features
—Fingerprint friction ridge details are generally described in a hierarchical order at three different levels, namely, Level 1 (pattern), Level 2 (minutia points), and Level 3 (p...
Anil K. Jain, Yi Chen, Meltem Demirkus
ICPR
2008
IEEE
15 years 8 months ago
A new hierarchical approach in robust real-time image feature detection and matching
Object recognition forms a ubiquitous problem in digital image processing. The detection of robust image features of high distinctiveness is one important key in this regard. We p...
Matthias Langer, Klaus-Dieter Kuhnert
145
Voted
CVPR
2009
IEEE
1378views Computer Vision» more  CVPR 2009»
16 years 8 months ago
A Novel Feature Descriptor Invariant to Complex Brightness Changes
We describe a novel and robust feature descriptor called ordinal spatial intensity distribution (OSID) which is invariant to any monotonically increasing brightness changes. Many t...
Feng Tang, Suk Hwan Lim, Nelson L. Chang, Hai Tao