Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Advanced Methods in Neural Computing
Advanced Methods in Neural Computing
An introduction to variable and feature selection
The Journal of Machine Learning Research
Robust Real-Time Face Detection
International Journal of Computer Vision
Experiments with AdaBoost.RT, an improved boosting scheme for regression
Neural Computation
Head Pose Estimation in Computer Vision: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Head Pose estimation on low resolution images
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
Neural network-based head pose estimation and multi-view fusion
CLEAR'06 Proceedings of the 1st international evaluation conference on Classification of events, activities and relationships
ICAPR'05 Proceedings of the Third international conference on Advances in Pattern Recognition - Volume Part I
Boost feature subset selection: a new gene selection algorithm for microarray dataset
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part II
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We present in this paper a new regression method adapted to problems dealing with a huge set of potential features like in pattern recognition. This method combines a boosted forward feature selection algorithm and a Generalized Regression Neural Network. The feature selection uses a new criterion, the Fuzzy Functional Criterion, to evaluate the relevance of each feature. It is well suited to measure to what extent a random variable y can be viewed as a function of another random variable x. We explain how this measure is more appropriate than the classical mutual information. At each step, features are evaluated using weights on examples computed from the error produced by the neural network at the previous step. This boosting strategy helps our system to focus on hard examples during the feature selection process. The application is head pose estimation, a challenging problem in pattern recognition. Test are carried out on the commonly used Pointing 04 database and compared with state-of-the-art results.