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» Highly Discriminative Invariant FEatures for Image Matching
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VISUAL
1999
Springer
13 years 8 months ago
Highly Discriminative Invariant FEatures for Image Matching
Abstract. In this paper, we present novel image-derived, invariant features that accurately capture both the geometric and color properties of an imaged object. These features can ...
Ronald-Bryan O. Alferez, Yuan-Fang Wang
BMVC
2002
13 years 7 months ago
Invariant Features from Interest Point Groups
This paper approaches the problem of finding correspondences between images in which there are large changes in viewpoint, scale and illumination. Recent work has shown that scale...
Matthew Brown, David G. Lowe
ICCV
2007
IEEE
14 years 6 months ago
Discriminant Embedding for Local Image Descriptors
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and visual recognition. However, such descriptors are generally par...
Gang Hua, Matthew Brown, Simon A. J. Winder
SCIA
2009
Springer
278views Image Analysis» more  SCIA 2009»
13 years 11 months ago
Rotation Invariant Image Description with Local Binary Pattern Histogram Fourier Features
In this paper, we propose Local Binary Pattern Histogram Fourier features (LBP-HF), a novel rotation invariant image descriptor computed from discrete Fourier transforms of local b...
Timo Ahonen, Jiri Matas, Chu He, Matti Pietikä...
CVPR
2007
IEEE
13 years 11 months ago
High Distortion and Non-Structural Image Matching via Feature Co-occurrence
We propose a novel approach for determining if a pair of images match each other under the effect of a highdistortion transformation or non-structural relation. The co-occurrence ...
Xi Chen, Tat-Jen Cham