Choosing Parameters of Kernel Subspace LDA for Recognition of Face Images Under Pose and Illumination Variations.
Jian HuangPong Chi YuenWensheng ChenJian-Huang LaiPublished in: IEEE Trans. Syst. Man Cybern. Part B (2007)
Keyphrases
- illumination variations
- face images
- face recognition
- principal component analysis
- feature extraction
- face recognition systems
- recognition rate
- recognition accuracy
- face recognition algorithms
- pose variations
- linear discriminant analysis
- feature space
- partial occlusion
- subspace methods
- image matching
- dimensionality reduction
- linear subspace
- discriminant analysis
- face databases
- subspace learning
- human faces
- low resolution
- face verification
- face pose
- illumination conditions
- facial expressions
- image set
- object recognition
- facial features
- pattern recognition
- low dimensional
- object tracking
- feature vectors
- sparse representation
- local binary pattern
- illumination normalization
- computer vision
- probe image
- lighting conditions
- input image
- data points
- high resolution
- training set
- image processing
- mean shift
- face detection
- high dimensional data
- image classification
- appearance variations
- feature selection