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ICPR
2006
IEEE
15 years 11 months ago
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning
It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
B. Michael Kelm, Chris Pal, Andrew McCallum
CVPR
2010
IEEE
14 years 10 months ago
High performance object detection by collaborative learning of Joint Ranking of Granules features
Object detection remains an important but challenging task in computer vision. We present a method that combines high accuracy with high efficiency. We adopt simplified forms of...
Chang Huang, Ramakant Nevatia
WACV
2005
IEEE
15 years 3 months ago
Multi-View Face Tracking with Factorial and Switching HMM
Dynamic face pose change and noise make it difficult to track multi-view faces in a cluttering environment. In this paper, we propose a graphical model based method, which combin...
Peng Wang, Qiang Ji
CVPR
2003
IEEE
15 years 11 months ago
Variational Inference for Visual Tracking
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
Jaco Vermaak, Neil D. Lawrence, Patrick Pér...
ICCV
2011
IEEE
13 years 9 months ago
An adaptive coupled-layer visual model for robust visual tracking
This paper addresses the problem of tracking objects which undergo rapid and significant appearance changes. We propose a novel coupled-layer visual model that combines the targe...
Luka Cehovin, Matej Kristan, Ales Leonardis