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ECCV
1994
Springer
13 years 11 months ago
Markov Random Field Models in Computer Vision
A variety of computer vision problems can be optimally posed as Bayesian labeling in which the solution of a problem is dened as the maximum a posteriori (MAP) probability estimate...
Stan Z. Li
ICRA
2010
IEEE
227views Robotics» more  ICRA 2010»
13 years 5 months ago
Efficient multi-view object recognition and full pose estimation
We present an approach for efficiently recognizing all objects in a scene and estimating their full pose from multiple views. Our approach builds upon a state of the art single-vie...
Alvaro Collet, Siddhartha S. Srinivasa
ICPR
2004
IEEE
14 years 8 months ago
Online Learning of Color Transformation for Interactive Object Recognition under Various Lighting Conditions
This paper describes an online learning method of color transformation for interactive object recognition. In order to recognize objects under various lighting conditions, the sys...
Nobutaka Shimada, Yasushi Makihara, Yoshiaki Shira...
VLDB
1990
ACM
69views Database» more  VLDB 1990»
13 years 11 months ago
Concept Description Language for Statistical Data Modeling
In this paper we describe a new language for statistical data modelling, which offers a general framework for the representation of elementary and summarydata.Thereare threemain c...
Tiziana Catarci, Giovanna D'Angiolini, Maurizio Le...
CVPR
2007
IEEE
14 years 9 months ago
Discriminant Additive Tangent Spaces for Object Recognition
Pattern variation is a major factor that affects the performance of recognition systems. In this paper, a novel manifold tangent modeling method called Discriminant Additive Tange...
Liang Xiong, Jianguo Li, Changshui Zhang