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» Learning the Compositional Nature of Visual Objects
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CVPR
2008
IEEE
14 years 9 months ago
Learning coupled conditional random field for image decomposition with application on object categorization
This paper proposes a computational system of object categorization based on decomposition and adaptive fusion of visual information. A coupled Conditional Random Field is develop...
Xiaoxu Ma, W. Eric L. Grimson
BVAI
2007
Springer
14 years 1 months ago
Neural Object Recognition by Hierarchical Learning and Extraction of Essential Shapes
We present a hierarchical system for object recognition that models neural mechanisms of visual processing identified in the mammalian ventral stream. The system is composed of ne...
Daniel Oberhoff, Marina Kolesnik
CVPR
2011
IEEE
13 years 3 months ago
Supervised Hierarchical Pitman-Yor Process for Natural Scene Segmentation
From conventional wisdom and empirical studies of annotated data, it has been shown that visual statistics such as object frequencies and segment sizes follow power law distributi...
Alex Shyr, Trevor Darrell, Michael Jordan, Raquel ...
ICIAP
2007
ACM
14 years 7 months ago
Natural scenes categorization by hierarchical extraction of typicality patterns
Natural scene categorization of images represents a very useful task for automatic image analysis systems in a wide variety of applications. In the literature, several methods hav...
Alessandro Perina, Marco Cristani, Vittorio Murino
AAAI
1998
13 years 9 months ago
Generating Coordinated Natural Language and 3D Animations for Complex Spatial Explanations
Dynamically providing students with clear explanations of complex spatial concepts is critical for a broad range of knowledge-based educational and training systems. This calls fo...
Stuart G. Towns, Charles B. Callaway, James C. Les...