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CVPR
2006
IEEE
14 years 9 months ago
Unsupervised Learning of Categories from Sets of Partially Matching Image Features
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Kristen Grauman, Trevor Darrell
CVPR
2009
IEEE
1517views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Linear Solution to Scale and Rotation Invariant Object Matching
Images of an object undergoing ego- or camera- motion often appear to be scaled, rotated, and deformed versions of each other. To detect and match such distorted patterns to a s...
Hao Jiang, Stella X. Yu
SCVMA
2004
Springer
14 years 23 days ago
Segregation of Moving Objects Using Elastic Matching
We present a method for figure-ground segregation of moving objects from monocular video sequences. The approach is based on tracking extracted contour fragments, in contrast to ...
Vishal Jain, Benjamin B. Kimia, Joseph L. Mundy
CVPR
2003
IEEE
14 years 9 months ago
Many-to-Many Graph Matching via Metric Embedding
Graph matching is an important component in many object recognition algorithms. Although most graph matching algorithms seek a one-to-one correspondence between nodes, it is often...
Yakov Keselman, Ali Shokoufandeh, M. Fatih Demirci...
ICIP
2010
IEEE
13 years 5 months ago
Learning image similarities via Probabilistic Feature Matching
In this paper, we propose a novel image similarity learning approach based on Probabilistic Feature Matching (PFM). We consider the matching process as the bipartite graph matchin...
Ziming Zhang, Ze-Nian Li, Mark S. Drew