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CVPR
2006
IEEE
14 years 3 months ago
Learning Joint Top-Down and Bottom-up Processes for 3D Visual Inference
We present an algorithm for jointly learning a consistent bidirectional generative-recognition model that combines top-down and bottom-up processing for monocular 3d human motion ...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...
PRL
2000
182views more  PRL 2000»
13 years 9 months ago
Bayesian MLP neural networks for image analysis
We demonstrate the advantages of using Bayesian multi layer perceptron (MLP) neural networks for image analysis. The Bayesian approach provides consistent way to do inference by c...
Aki Vehtari, Jouko Lampinen
ICCV
2007
IEEE
14 years 11 months ago
Optimization and Learning for Registration of Moving Dynamic Textures
We address the problem of registering a sequence of images in a moving dynamic texture video. This involves optimization with respect to camera motion, the average image, and the ...
Junzhou Huang, Xiaolei Huang, Dimitris N. Metaxas
ICRA
2009
IEEE
173views Robotics» more  ICRA 2009»
14 years 3 months ago
Most salient region tracking
— In this paper, we introduce a cognitive approach for object tracking from a mobile platform. The approach is based on a biologically motivated attention system which is able to...
Simone Frintrop, Markus Kessel
CVPR
2008
IEEE
14 years 11 months ago
Context and observation driven latent variable model for human pose estimation
Current approaches to pose estimation and tracking can be classified into two categories: generative and discriminative. While generative approaches can accurately determine human...
Abhinav Gupta, Trista Chen, Francine Chen, Don Kim...