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» The Pyramid Match: Efficient Learning with Partial Correspon...
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CVPR
2007
IEEE
15 years 1 months ago
Pyramid Match Hashing: Sub-Linear Time Indexing Over Partial Correspondences
Matching local features across images is often useful when comparing or recognizing objects or scenes, and efficient techniques for obtaining image-to-image correspondences have b...
Kristen Grauman, Trevor Darrell
ICPR
2008
IEEE
15 years 6 days ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
CVPR
2006
IEEE
15 years 1 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
2006
IEEE
15 years 1 months ago
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories
This paper presents a method for recognizing scene categories based on approximate global geometric correspondence. This technique works by partitioning the image into increasingl...
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce