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2 results on '"game-theoretic matching"'

1. An Online Three-Stage Method for Facial Point Localization

Author

Ni, Weiyuan, Vu, Ngoc-Son, Caplier, Alice, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Nierstrasz, Oscar, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Sudan, Madhu, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Vardi, Moshe Y., Series editor, Weikum, Gerhard, Series editor, Real, Pedro, editor, Diaz-Pernil, Daniel, editor, Molina-Abril, Helena, editor, Berciano, Ainhoa, editor, and Kropatsch, Walter, editor

Published
2011
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2. An Online Three-stage Method for Facial Point Localization

Author

Alice Caplier, Weiyuan Ni, Ngoc-Son Vu, ACROE - Ingénierie de la Création Artistique (ACROE-ICA), Ministère de la Culture et de la Communication (MCC)-Institut National Polytechnique de Grenoble (INPG), GIPSA - Architecture, Géométrie, Perception, Images, Gestes (GIPSA-AGPIG), Département Images et Signal (GIPSA-DIS), Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Grenoble Images Parole Signal Automatique (GIPSA-lab), Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS)-Université Stendhal - Grenoble 3-Université Pierre Mendès France - Grenoble 2 (UPMF)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Centre National de la Recherche Scientifique (CNRS), Pedro Real, Daniel Diaz-Pernil, Helena Molina-Abril, Ainhoa Berciano, and Walter Kropatsch

Subjects
Face hallucination, facial point localization, business.industry, ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, POEM, 020207 software engineering, Pattern recognition, 02 engineering and technology, Expression (mathematics), Set (abstract data type), Spatial relation, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Feature (computer vision), Computer Science::Computer Vision and Pattern Recognition, Histogram, Face (geometry), 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Computer vision, Enhanced Data Rates for GSM Evolution, Artificial intelligence, game-theoretic matching, business, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Mathematics
Abstract

Poster session: Biometrics; International audience; Finding facial features respectively under expression and illumination variations is always a difficult problem. One popular solution for improving the performance of facial point localization is to use the spatial relation between facial feature positions. While existing algorithms mostly rely on the priori knowledge of facial structure and on a training phase, this paper presents an online approach without requirements of pre-defined constraints on feature distributions. Instead of training specific detectors for each facial feature, a generic method is first used to extract a set of interest points from test images. With a robust feature descriptor named Patterns Oriented Edge Magnitude (POEM), a smaller set of these points are picked as candidates. Then we apply a game-theoretic technique to select facial points from the candidates, while the global geometric properties of face are well preserved. The experimental results demonstrate that our method achieves satisfactory performance for face images under expression and lighting variations

Published
2011
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