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ICCV
2007
IEEE
14 years 7 months ago
How Good are Local Features for Classes of Geometric Objects
Recent work in object categorization often uses local image descriptors such as SIFT to learn and detect object categories. Such descriptors explicitly code local appearance and h...
Michael Stark, Bernt Schiele
GECCO
2005
Springer
120views Optimization» more  GECCO 2005»
13 years 11 months ago
Exploiting gradient information in numerical multi--objective evolutionary optimization
Various multi–objective evolutionary algorithms (MOEAs) have obtained promising results on various numerical multi– objective optimization problems. The combination with gradi...
Peter A. N. Bosman, Edwin D. de Jong
CLOR
2006
13 years 9 months ago
A Discriminative Framework for Texture and Object Recognition Using Local Image Features
This chapter presents an approach for texture and object recognition that uses scale- or affine-invariant local image features in combination with a discriminative classifier. Text...
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce
PAMI
2012
11 years 8 months ago
LDAHash: Improved Matching with Smaller Descriptors
—SIFT-like local feature descriptors are ubiquitously employed in such computer vision applications as content-based retrieval, video analysis, copy detection, object recognition...
Christoph Strecha, Alexander A. Bronstein, Michael...
CCIA
2007
Springer
13 years 12 months ago
An Evaluation of an Object Recognition Schema Using Multiple Region Detectors
Abstract. Robust object recognition is one of the most challenging topics in computer vision. In the last years promising results have been obtained using local regions and descrip...
Meritxell Vinyals, Arnau Ramisa, Ricardo Toledo