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» Learning Robust Objective Functions with Application to Face...
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AVSS
2006
IEEE
13 years 10 months ago
Classification-Based Likelihood Functions for Bayesian Tracking
The success of any Bayesian particle filtering based tracker relies heavily on the ability of the likelihood function to discriminate between the state that fits the image well an...
Chunhua Shen, Hongdong Li, Michael J. Brooks
TEC
2008
104views more  TEC 2008»
13 years 6 months ago
Coevolution of Fitness Predictors
Abstract--We present an algorithm that coevolves fitness predictors, optimized for the solution population, which reduce fitness evaluation cost and frequency, while maintaining ev...
Michael D. Schmidt, Hod Lipson
BMVC
2001
13 years 9 months ago
A Buyer's Guide to Euclidean Elliptical Cylindrical and Conical Surface Fitting
The ability to construct CAD or other object models from edge and range data has a fundamental meaning in building a recognition and positioning system. While the problem of model...
Petko Faber, Robert B. Fisher
ICB
2009
Springer
134views Biometrics» more  ICB 2009»
14 years 1 months ago
A Model Based Approach for Expressions Invariant Face Recognition
This paper describes an idea of recognizing the human face in the presence of strong facial expressions using model based approach. The features extracted for the face image sequen...
Zahid Riaz, Christoph Mayer, Matthias Wimmer, Mich...
CVPR
2007
IEEE
14 years 8 months ago
Filtered Component Analysis to Increase Robustness to Local Minima in Appearance Models
Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis...
Fernando De la Torre, Alvaro Collet, Manuel Quero,...