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» Improved SIFT-Features Matching for Object Recognition
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GBRPR
2007
Springer
13 years 11 months ago
Constellations and the Unsupervised Learning of Graphs
Abstract. In this paper, we propose a novel method for the unsupervised clustering of graphs in the context of the constellation approach to object recognition. Such method is an E...
Boyan Bonev, Francisco Escolano, Miguel Angel Loza...
CVPR
2012
IEEE
11 years 10 months ago
Locality-constrained and spatially regularized coding for scene categorization
Improving coding and spatial pooling for bag-of-words based feature design have gained a lot of attention in recent works addressing object recognition and scene classification. ...
Aymen Shabou, Hervé Le Borgne
ICPR
2008
IEEE
14 years 8 months 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
1996
IEEE
13 years 11 months ago
Pattern Rejection
The e ciency of pattern recognition is particularly crucial in two scenarios; whenever there are a large number of classes to discriminate, and, whenever recognition must be perfo...
Simon Baker, Shree K. Nayar
ICIP
2004
IEEE
14 years 9 months ago
A motion field reconstruction scheme for smooth boundary video object segmentation
Motion segmentation is a classic and on-going research topic which is an important pre-stage for many video processes. The reliability of the motion field calculation directly dete...
Jean Gao, Ninad Thakoor, Sungyong Jung