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Paper Detail

Paper:	SS-1.3
Session:	Statistical Inferences on Nonlinear Manifolds with Applications in Signal and Image Processing
Time:	Tuesday, May 16, 11:10 - 11:30
Presentation:	Special Session Lecture
Topic:	Special Sessions: Statistical inferences on nonlinear manifolds with applications in signal and image processing
Title:	3D FACE RECOGNITION USING SHAPES OF FACIAL CURVES
Authors:	Chafik Samir, ENIC Telecom-Lille1, France; Anuj Srivastava, Florida State University, United States; Mohamed Daoudi, ENIC Telecom-Lille1, France
Abstract:	Recognition of human beings using shapes of their full facial surfaces is a difficult problem. Our approach is to approximate a facial surface using a collection of (closed) facial curves, and to compare surfaces by comparing their corresponding curves. The differences between shapes of curves are quantified using lengths of geodesic paths between them on a pre-defined curve shape space. The metric for comparing facial surfaces is a composition of the metric involving individual facial curves. These ideas are demonstrated in the context of face recognition using the nearest-neighbor classifier.