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ICPR
2010
IEEE
14 years 12 days ago
A Unified Probabilistic Approach to Feature Matching and Object Segmentation
This paper deals with feature matching and segmentation of common objects in a pair of images, simultaneously. For the feature matching problem, the matching likelihoods of all fea...
Tae Hoon Kim (Seoul National University), Kyoung M...
ICCV
2009
IEEE
1821views Computer Vision» more  ICCV 2009»
14 years 10 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...
MIR
2006
ACM
145views Multimedia» more  MIR 2006»
13 years 11 months ago
Similarity learning via dissimilarity space in CBIR
In this paper, we introduce a new approach to learn dissimilarity for interactive search in content based image retrieval. In literature, dissimilarity is often learned via the fe...
Giang P. Nguyen, Marcel Worring, Arnold W. M. Smeu...
CVPR
2007
IEEE
14 years 7 months ago
Image Matching via Saliency Region Correspondences
We introduce the notion of co-saliency for image matching. Our matching algorithm combines the discriminative power of feature correspondences with the descriptive power of matchi...
Alexander Toshev, Jianbo Shi, Kostas Daniilidis
CVPR
2005
IEEE
14 years 7 months ago
Efficient Image Matching with Distributions of Local Invariant Features
Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature set...
Kristen Grauman, Trevor Darrell