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» Learning Hierarchical Models of Scenes, Objects, and Parts
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ECCV
2006
Springer
15 years 11 months ago
Learning Compositional Categorization Models
Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
Björn Ommer, Joachim M. Buhmann
85
Voted
ECCV
2006
Springer
15 years 11 months ago
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
This paper introduces the Located Hidden Random Field (LHRF), a conditional model for simultaneous part-based detection and segmentation of objects of a given class. Given a traini...
Ashish Kapoor, John M. Winn
CVPR
2009
IEEE
1413views Computer Vision» more  CVPR 2009»
16 years 4 months ago
Learning Semantic Scene Models by Object Classification and Trajectory Clustering
The visual surveillance task is to monitor the activity of objects in a scene. In far-field settings (i.e., wide outdoor areas), the majority of visible activities are objects movi...
Hanqing Lu, Stan Z. Li, Tianzhu Zhang
NN
2002
Springer
114views Neural Networks» more  NN 2002»
14 years 9 months ago
Learning the parts of objects by auto-association
Recognition-by-components is one of the possible strategies proposed for object recognition by the brain, but little is known about the low-level mechanism by which the parts of o...
Xijin Ge, Shuichi Iwata
81
Voted
PAMI
2007
193views more  PAMI 2007»
14 years 9 months ago
Robust Object Recognition with Cortex-Like Mechanisms
—We introduce a new general framework for the recognition of complex visual scenes, which is motivated by biology: We describe a hierarchical system that closely follows the orga...
Thomas Serre, Lior Wolf, Stanley M. Bileschi, Maxi...