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Two- and Three-Dimensional Patterns of the Face [Kietas viršelis]

  • Formatas: Hardback, 272 pages, aukštis x plotis: 229x152 mm, weight: 660 g
  • Išleidimo metai: 15-Jun-1999
  • Leidėjas: A K Peters
  • ISBN-10: 1568810873
  • ISBN-13: 9781568810874
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 272 pages, aukštis x plotis: 229x152 mm, weight: 660 g
  • Išleidimo metai: 15-Jun-1999
  • Leidėjas: A K Peters
  • ISBN-10: 1568810873
  • ISBN-13: 9781568810874
Kitos knygos pagal šią temą:
The human face is perhaps the most familiar and easily recognized object in the world, yet both its three-dimensional shape and its two-dimensional images are complex and hard to characterize. This book develops the vocabulary of ridges and parabolic curves, of illumination eigenfaces and elastic warpings for describing the perceptually salient features of a face and its images. The book also explores the underlying mathematics and applies these mathematical techniques to the computer vision problem of face recognition, using both optical and range images.
Preface vii
Faces from Pattern-Theoretic Perspective
1(20)
Pattern Theory
1(2)
Three Universal Classes of Stochastic Models
3(5)
Bayes Probability Theory: Pattern Analysis and Pattern Synthesis
8(4)
Pattern Theory Architectures
12(1)
And How about the Face?
13(8)
Overview of Approaches to Face Recognition
21(24)
Computer Vision Theory of Face Recognition
21(4)
Facial Features via Filters
25(2)
A Deformable Template Approach to Facial Features
27(4)
Gaussian Models of Whole Faces
31(4)
Face Warps
35(4)
Three-Dimensional Face Models
39(6)
Modeling Variations in Illumination
45(34)
Linear Models for Lighting Variation
45(3)
Constructing the Lighting Model
48(3)
The Experiment
51(3)
Results
54(18)
Generating 3-D Face Models from Illumination Variation
72(7)
Modeling Variations in Geometry
79(26)
Global and Local Wraps
79(4)
A Robust Treatment of Intensity Differences
83(2)
The Global Warp
85(4)
Homogenous Local Warping
89(13)
Inhomogenous Local Warping
102(3)
Recognition from Image Data
105(20)
The Energy Functional
105(2)
The Algorithm
107(2)
Results
109(16)
Parabolic Curves and Ridges on Surfaces
125(40)
Overview
125(3)
Monge Patches
128(3)
Contact with Planes
131(5)
Contact with Spheres; Ridge Points
136(15)
Umbilics
151(11)
The Road Map
162(3)
Sculpting a Surface
165(36)
Overview
165(1)
Transitions
165(11)
The Evolution of the Bell and the Dimple
176(6)
How to Sculpt a Face
182(19)
Finding Facial Features from Range Data
201(16)
Nose Ridge
203(1)
Eye Features: The Application of Symmetry Constraints
204(6)
Bounding Regions of Convex Structures
210(3)
Face/Non-Face Segmentation
213(4)
Recognition from Range Data
217(24)
Recognition by Depth Template Comparison
217(6)
Scalar Features from 3-D Data
223(3)
The Algorithm
226(3)
Experimental Results
229(12)
What's Next?
241(8)
Modeling the 2D Image
241(2)
Stochastic Models for Shape
243(6)
References 249(11)
Index 260


Hallinan, Peter W.; Gordon, Gaile; Yuille, A. L.; Giblin, Peter; Mumford, David