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CVPR
2007
IEEE
16 years 5 months ago
Composite Models of Objects and Scenes for Category Recognition
This paper presents a method of learning and recognizing generic object categories using part-based spatial models. The models are multiscale, with a scene component that specifie...
David J. Crandall, Daniel P. Huttenlocher
ECCV
2008
Springer
16 years 5 months ago
Keypoint Signatures for Fast Learning and Recognition
Abstract. Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the ...
Michael Calonder, Vincent Lepetit, Pascal Fua
128
Voted
GECCO
2003
Springer
126views Optimization» more  GECCO 2003»
15 years 8 months ago
Coevolution and Linear Genetic Programming for Visual Learning
In this paper, a novel genetically-inspired visual learning method is proposed. Given the training images, this general approach induces a sophisticated feature-based recognition s...
Krzysztof Krawiec, Bir Bhanu
150
Voted
TIP
2008
287views more  TIP 2008»
15 years 3 months ago
3-D Object Recognition Using 2-D Views
We consider the problem of recognizing 3-D objects from 2-D images using geometric models and assuming different viewing angles and positions. Our goal is to recognize and localize...
Wenjing Li, George Bebis, Nikolaos G. Bourbakis
109
Voted
CVPR
2010
IEEE
1248views Computer Vision» more  CVPR 2010»
15 years 12 months ago
Food Recognition Using Statistics of Pairwise Local Features
Food recognition is difficult because food items are deformable objects that exhibit significant variations in appearance. We believe the key to recognizing food is to exploit the...
Shulin Yang, Mei Chen, Dean Pomerleau, Rahul Sukth...