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» Object Recognition Using Segmentation for Feature Detection
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PR
2008
173views more  PR 2008»
13 years 7 months ago
Object recognition using a generalized robust invariant feature and Gestalt's law of proximity and similarity
In this paper, we propose a new context-based method for object recognition. We first introduce a neuro-physiologically motivated visual part detector. We found that the optimal f...
Sungho Kim, Kuk-Jin Yoon, In-So Kweon
IJCV
2008
241views more  IJCV 2008»
13 years 7 months ago
Object Class Recognition and Localization Using Sparse Features with Limited Receptive Fields
We investigate the role of sparsity and localized features in a biologically-inspired model of visual object classification. As in the model of Serre, Wolf, and Poggio, we first a...
Jim Mutch, David G. Lowe
ICDAR
2003
IEEE
14 years 1 months ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...
ICPR
2000
IEEE
14 years 3 days ago
Segmentation and Surface Characterization of Arbitrary 3D Meshes for Object Reconstruction and Recognition
Polygonal models are the most common representation of structured 3D data in computer graphics, pattern recognition and machine vision. The method presented here automatically ide...
Georgios Papaioannou, Evaggelia-Aggeliki Karabassi...
ICPR
2008
IEEE
14 years 2 months ago
Novel image feature alphabets for object recognition
Most successful object recognition systems are based on a visual alphabet of quantised gradient orientations. Here, we introduce two richer image feature alphabets for use in obje...
Martin Lillholm, Lewis D. Griffin