Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Pairwise classification and support vector machines
Advances in kernel methods
Two- and three-dimensional patterns of the face
Two- and three-dimensional patterns of the face
Computational anatomy: an emerging discipline
Quarterly of Applied Mathematics - Special issue on current and future challenges in the applications of mathematics
Looking at People: Sensing for Ubiquitous and Wearable Computing
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Optimal Linear Representations of Images for Object Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Journal of Cognitive Neuroscience
Fast and robust fixed-point algorithms for independent component analysis
IEEE Transactions on Neural Networks
Semi-random subspace method for face recognition
Image and Vision Computing
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This paper investigates the use of range images of faces for recognizing people. 3D scans of faces lead to range images that are linearly projected to low-dimensional subspaces for use in a classifier, say a nearest neighbor classifier or a support vector machine, to label people. Learning of subspaces is performed using an optimal component analysis, i.e. a stochastic optimization algorithm (on a Grassmann manifold) to find a subspace that maximizes classifier performance on the training image set. Results are presented for face recognition using FSU face database, and are compared with standard component anlyses such as PCA and ICA. This provides an efficient tool for analyzing certain aspects of facial shapes while avoiding a difficult task of geometric surface modeling.