Book contents
- Frontmatter
- Contents
- Contributors
- Part I Identification of the Living
- Chapter 1 Familiar face recognition
- Chapter 2 Unfamiliar face recognition
- Chapter 3 EFIT-V
- Chapter 4 Facial recall and computer composites
- Chapter 5 Facial ageing
- Chapter 6 Age progression and regression
- Chapter 7 Computer-assisted age progression
- Chapter 8 Facial recognition from identification parades
- Chapter 9 Virtual human identification line-ups
- Chapter 10 Computer-generated face models
- Chapter 11 Recognising and learning faces in motion
- Chapter 12 Facial image comparison
- Chapter 13 Three-dimensional facial imaging
- Part II Identification of the Dead
- Index
- Plate Section
- References
Chapter 10 - Computer-generated face models
Published online by Cambridge University Press: 05 May 2012
Book contents
- Frontmatter
- Contents
- Contributors
- Part I Identification of the Living
- Chapter 1 Familiar face recognition
- Chapter 2 Unfamiliar face recognition
- Chapter 3 EFIT-V
- Chapter 4 Facial recall and computer composites
- Chapter 5 Facial ageing
- Chapter 6 Age progression and regression
- Chapter 7 Computer-assisted age progression
- Chapter 8 Facial recognition from identification parades
- Chapter 9 Virtual human identification line-ups
- Chapter 10 Computer-generated face models
- Chapter 11 Recognising and learning faces in motion
- Chapter 12 Facial image comparison
- Chapter 13 Three-dimensional facial imaging
- Part II Identification of the Dead
- Index
- Plate Section
- References
Summary
Introduction
The rapid progress in digital image capture and computer processing power has provided new opportunities for the analysis and synthesis of facial shape and appearance. New algorithms have been developed to exploit these improvements and have found applications in health, security and forensics. In this chapter some of the main techniques that have been developed to capture, model and process facial image data are reviewed.
Data capture
Photography
The simplest technique for capturing facial image data is photography. There have been rapid improvements in the resolution of digital cameras, so that the quality of direct digital capture equals or even exceeds chemical film. While two-dimensional (2D) images present the simplest method for facial image capture, 2D data present a number of problems when it comes to analysing and processing the data. Faces are inherently 3D in nature and the projection to 2D can introduce variation in the appearance that is not intrinsic to the faces themselves. Even small changes in the facial orientation can produce a vastly different projected 2D facial shape. Changes in lighting are also difficult to model and remove using purely 2D methods.
- Type
- Chapter
- Information
- Craniofacial Identification , pp. 115 - 124Publisher: Cambridge University PressPrint publication year: 2012
References
2002 Multilinear analysis of image ensembles: TensorFacesLecture Notes in Computer Science 2350 447Google Scholar
2007 Optimal step nonrigid ICP algorithms for surface registrationComputer Vision and Pattern Recognition 2007 1Google Scholar
2008 Physically based finite element model of the faceBiomedical Simulation, Lecture Notes in Computer Science 5104 1Google Scholar
1997 Eigenfaces vs. Fisherfaces: recognition using class specific linear projectionIEEE Transactions on Pattern Analysis and Machine Intelligence 19 711Google Scholar
2004 Real-time finite element modeling for surgery simulation: an application to virtual suturingIEEE Transactions on Visualization and Computer Graphics 10 314Google Scholar
1992 A method for registration of 3-D shapesIEEE Transactions Pattern Analysis and Machine Intelligence 14 239Google Scholar
1999
1989 Principal warps: thin plate splines and the decomposition of deformationsIEEE Transactions Pattern Analysis and Machine Intelligence, 11 567Google Scholar
1997 Landmark methods for forms without landmarks: localizing group differences in outline shapeMedical Image Analysis 1 225Google Scholar
2001 Active appearance modelsIEEE Transactions Pattern Analysis and Machine Intelligence 23 681Google Scholar
1977 NMR in cancer: XVI. Fonar image of the live human bodyPhysiological Chemistry and Physics 9 97Google Scholar
2008 Statistical Models of Shape – Optimisation and EvaluationBerlinSpringer
2008 Groupwise surface correspondence by optimization: Representation and regularizationMedical Image Analysis 12 787Google Scholar
1988
1998 Statistical Shape AnalysisChichesterJohn Wiley and Sons
2008
2004 Principal geodesic analysis for the study of nonlinear statistics of shapeIEEE Transactions on Medical Imaging 23 995Google Scholar
1996 Image Fusion and Shape VariabilityLeedsUniversity of Leeds Press
1985 Computational experiments with a feature based stereo algorithmIEEE Transactions Pattern Analysis and Machine Intelligence 7 17Google Scholar
2009 Validating a voxel-based finite element model of a human mandible using digital speckle pattern interferometryJournal of Biomechanics 42 1224Google Scholar
1977 Radiographic thin-section image of the human wrist by nuclear magnetic resonanceNature 270 722Google Scholar
2009
1983 A perspective on range finding techniques for computer visionIEEE Transactions Pattern Analysis and Machine Intelligence PAMI-5 2 122Google Scholar
1994 A stereo matching algorithm with an adaptive window: Theory and experimentIEEE Transactions Pattern Analysis and Machine Intelligence 16 9Google Scholar
1996 Craniofacial surgery simulationProceedings Visualization in Biomedical Computing, Lecture Notes in Computer Science 1131 541Google Scholar
1996
2009 Masticatory loading and bone adaptation in the supraorbital torus of developing macaquesAmerican Journal of Physical Anthropology 139 193Google Scholar
1986 A finite element model of skin deformation. II. An experimental model of skin deformationLaryngoscope 96 406Google Scholar
1987 Marching cubes: a high resolution 3D surface construction algorithmComputer Graphics 21 163Google Scholar
2006 Expression transfer between photographs through multilinear AAM’sComputer Graphic and Image Processing 06 239Google Scholar
2009 Assessment of the role of sutures in a lizard skull – a computer modelling studyProceedings of the Royal Society 276 39Google Scholar
1998 A new volumetric CT machine for dental imaging based on the cone-beam technique: preliminary resultsEuropean Radiology 8 9Google Scholar
2006 Differences between sliding semi-landmark methods in geometric morphometrics, with an application to human craniofacial and dental variationJournal of Anatomy 208 769Google Scholar
1995 A finite element facial model for simulating plastic surgeryPlastic Reconstructive Surgery 96 1100Google Scholar
1999 Kernel principal component analysisAdvances in Kernel Methods – Support Vector LearningCambridge, MAMIT Press
2004 A combined landmark and outline-based approach to ontogenetic shape change in the Ordovician Trilobite Applications of Morphometrics in Paleontology and Biology67New YorkSpringer
2003
2009 An efficient stochastic approach to groupwise non-rigid image registrationProceedings of Computer Vision and Pattern Recognition 2009 2208Google Scholar
1984 Automated phase-measuring profilometry of 3-D diffuse objectsApplied Optics 23 3105Google Scholar
1990 Physically-based facial modeling, analysis, and animationJournal of Visualization and Computer Animation 1 73Google Scholar
2001 Computer graphics in facial perception researchIEEE Computer Graphics and Applications 21 42Google Scholar
2007
2005 Towards realism in facial transformation: results of a wavelet MRF methodComputer Graphics Forums 24 1Google Scholar
2000 3D Imaging in MedicineBoca Raton, FLCRC Press
1997 Linear object classes and image synthesis from a single example imageIEEE IEEE Transactions Pattern Analysis and Machine Intelligence 19 733Google Scholar
2006 Computer-assisted planning in cranio-maxillofacial surgeryJournal of Computing and Information Technology – CIT1453Google Scholar
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