E-Book, Englisch, 304 Seiten, eBook
Reihe: Image Processing, Computer Vision, Pattern Recognition, and Graphics
Zhou / Zhao / Tang Analysis and Modeling of Faces and Gestures
2007
ISBN: 978-3-540-75690-3
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
Third International Workshop, AMFG 2007 Rio de Janeiro, Brazil, October 20, 2007 Proceedings
E-Book, Englisch, 304 Seiten, eBook
Reihe: Image Processing, Computer Vision, Pattern Recognition, and Graphics
ISBN: 978-3-540-75690-3
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark
Zielgruppe
Research
Autoren/Hrsg.
Weitere Infos & Material
Oral - I.- Learning Personal Specific Facial Dynamics for Face Recognition from Videos.- A New Probabilistic Model for Recognizing Signs with Systematic Modulations.- Model-Based Stereo with Occlusions.- View Invariant Head Recognition by Hybrid PCA Based Reconstruction.- Poster - I.- Person-Independent Monocular Tracking of Face and Facial Actions with Multilinear Models.- Automatic Facial Expression Recognition Using Boosted Discriminatory Classifiers.- Generating Body Surface Deformation Using Level Set Method.- Patch-Based Pose Inference with a Mixture of Density Estimators.- Integrating Multiple Visual Cues for Robust Real-Time 3D Face Tracking.- Model-Assisted 3D Face Reconstruction from Video.- Human Perambulation as a Self Calibrating Biometric.- Oral - II.- Detecting, Localizing and Classifying Visual Traits from Arbitrary Viewpoints Using Probabilistic Local Feature Modeling.- Enhanced Local Texture Feature Sets for Face Recognition Under Difficult Lighting Conditions.- Structured Ordinal Features for Appearance-Based Object Representation.- SODA-Boosting and Its Application to Gender Recognition.- Poster - II.- Single Image Subspace for Face Recognition.- Human Face Processing with 1.5D Models.- Fusing Gabor and LBP Feature Sets for Kernel-Based Face Recognition.- A Unified Framework of Subspace and Distance Metric Learning for Face Recognition.- Face Recognition Based on Pose-Variant Image Synthesis and Multi-level Multi-feature Fusion.- Towards Pose-Invariant 2D Face Classification for Surveillance.- Robust Face Recognition Strategies Using Feed-Forward Architectures and Parts.