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» A New Bayesian Framework for Object Recognition
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CVPR
1999
IEEE
13 years 9 months ago
A New Bayesian Framework for Object Recognition
We introduce an approach to feature-based object recognition, using maximum a posteriori (MAP) estimation under a Markov random field (MRF) model. This approach provides an effici...
Yuri Boykov, Daniel P. Huttenlocher
ICCV
2003
IEEE
14 years 6 months ago
A Bayesian Network Framework for Relational Shape Matching
A Bayesian network formulation for relational shape matching is presented. The main advantage of the relational shape matching approach is the obviation of the non-rigid spatial m...
Anand Rangarajan, James M. Coughlan, Alan L. Yuill...
ICPR
2004
IEEE
14 years 5 months ago
A Fast Discriminant Approach to Active Object Recognition and Pose Estimation
This paper presents a new criterion for viewpoint selection in the context of active Bayesian object recognition and pose estimation. Recognition is performed by probabilistically...
Catherine Laporte, Rupert Brooks, Tal Arbel
SSIAI
2000
IEEE
13 years 9 months ago
A New Bayesian Relaxation Framework for the Estimation and Segmentation of Multiple Motions
In this paper we propose a new probabilistic relaxation framework to perform robust multiple motion estimation and segmentation from a sequence of images. Our approach uses displa...
Alexander Strehl, Jake K. Aggarwal
CVPR
2000
IEEE
13 years 9 months ago
Adaptive Bayesian Recognition in Tracking Rigid Objects
We present a framework for tracking rigid objects based on an adaptive Bayesian recognition technique that incorporates dependencies between object features. At each frame we fin...
Yuri Boykov, Daniel P. Huttenlocher