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ICCV
2005
IEEE
14 years 2 months ago
Learning Hierarchical Models of Scenes, Objects, and Parts
We describe a hierarchical probabilistic model for the detection and recognition of objects in cluttered, natural scenes. The model is based on a set of parts which describe the e...
Erik B. Sudderth, Antonio B. Torralba, William T. ...
SIGIR
2008
ACM
13 years 8 months ago
Hierarchical naive bayes models for representing user profiles
In this paper, we show how a user profile can be enhanced when a more detailed description of the products is included. Two main assumptions have been considered: the first implie...
Juan F. Huete, Luis M. de Campos, Juan M. Fern&aac...
ICRA
2006
IEEE
128views Robotics» more  ICRA 2006»
14 years 2 months ago
Probabilistic Location Recognition using Reduced Feature Set
Abstract— The localization capability is central to basic navigation tasks and motivates development of various visual navigation systems. In this paper we describe a two stage a...
Fayin Li, Jana Kosecka
JMM2
2007
127views more  JMM2 2007»
13 years 8 months ago
Robust Face Recognition through Local Graph Matching
— A novel face recognition method is proposed, in which face images are represented by a set of local labeled graphs, each containing information about the appearance and geometr...
Ehsan Fazl Ersi, John S. Zelek, John K. Tsotsos
ICCV
2001
IEEE
14 years 10 months ago
A Gabor Feature Classifier for Face Recognition
This paper describes a novel Gabor Feature Class$er (GFC)method forface recognition. The GFC method employs an enhanced Fisher discrimination model on an augmented Gabor feature v...
Chengjun Liu, Harry Wechsler