Boosting Local Feature Based Classifiers for Face Recognition.
Lei ZhangStan Z. LiZhi Yi QuXiangsheng HuangPublished in: CVPR Workshops (2004)
Keyphrases
- face recognition
- randomized trees
- ensemble learning
- weak classifiers
- adaboost algorithm
- boosting algorithms
- face detection
- weak learners
- ensemble classifier
- boosted classifiers
- improving classification accuracy
- feature selection
- boosting framework
- strong classifier
- majority voting
- decision stumps
- ensemble classification
- naive bayes
- linear classifiers
- ensemble methods
- subspace methods
- decision trees
- support vector
- face images
- training data
- recognition rate
- multiple classifier systems
- discriminant analysis
- weighted voting
- multiclass classification
- accurate classifiers
- discriminative classifiers
- test set
- sparse representation
- bayesian classifiers
- cost sensitive
- human faces
- svm classifier
- loss function
- machine learning algorithms
- computer vision
- combining classifiers
- improve recognition accuracy
- binary classification problems
- base classifiers
- local binary pattern
- classification accuracy
- classifier combination
- random forests
- classification models
- feature subset
- feature set
- principal component analysis
- facial expressions
- multi class
- support vector machine
- training set
- machine learning