Face Recognition

I : Lectures (lecturer's name printed in bold face).- Neural and Psychophysical Analysis of Object and Face Recognition.- Multi-Modal Person Authentication.- Human Face Perception and Identification.- Discriminant Analysis of Principal Components for Face Recognition.- Inductive Principles for Learning from Data.- Phenotypic Versus Genotypic Approaches to Face Recognition.- Connectionist Methods for Human Face Processing.- Efficient Focusing and Face Detection.- Face Detection and Recognition.- The Bochum/USC Face Recognition System.- Face Recognition Using Deformable Matching.- Beyond Linear Eigenspaces: Bayesian Matching for Face Recognition.- The FERET Evaluation.- Active Vision-based Face Recognition: Issues, Applications and Techniques.- Getting Facial Features and Gestures in 3D.- Generalization to Novel Views from a Single Face Image.- Modular Forensic Architectures.- Eye Detection and Face Recognition Using Evolutionary Computation.- II : Participant Presentations (participant's name printed in bold face).- Learning Viewpoint Invariant Face Representations from Visual Experience by Temporal Association.- Visible Speech Perception and Robustness in Face Processing.- Practical Applications of Facial Recognition: Automated Facial Recognition Access Control System.- Estimating 3D Facial Pose Using the EM Algorithm.- PCA, Neural Networks and Estimation for Face Detection.- 3D Pose Estimation of the Face from Video.- Characterizing Virtual Eigensignatures for General Purpose Face Recognition.- An Attentive Processing Strategy for the Analysis of Facial Features.- Face Location in Real Backgrounds.- Recognizing People and Behaviors.- Differences of Face and Object Recognition in Utilizing Early Visual Information.- Pulse Images for Face Recognition.- Faceless Identification.- Pose Discrimination and Eye Detection Using Support Vector Machines (SVM).- A Practical Automatic Face Recognition System.- Feature Processing from Upright and Inverted Faces.- Using