| Description |
viii, 370 pages |
| Series |
World Scientific series in computer science ; v. 32 |
|
Series in computer science ; v. 32
|
| Contents |
Table of Contents; Preface; Minimal Subset Random Sampling for Pose Determination and Refinement; 1 Introduction; 2 Previous Approaches; 3 Optimization Model; 4 Minimal Subset Random Sampling; 4.1 Computing a Hypothetical Pose; 5 Solving Nonlinear Polynomial Systems; 6 Examples; 7 Parallelization; 8 Discussion and Conclusions; Acknowledgements; References; Robust High Breakdown Estimation and Consensus; 1 Introduction; 2 The Weighted Least Squares Estimator; 3 The Least Median of Squares Estimator; 3.1 The LMedS Algorithm; 3.2 Performance Analysis; 4 The Consensus Paradigm; 5 Conclusion |
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1 Introduction: Time-Frequency Space1.1 Brief Overview; 1.2 The Fourier Operator; 1.3 Gabor's ""logon"" paradigm; 1.4 Wavelets; 2 ""Wavelets"" versus Wavelets; 3 The TF-affine Chirplet; 3.1 Linearly Varying Instantaneous Frequency; 3.2 ""Le Pépielette""; ""The Chirplet""; 3.3 TF-Affine Geometry; 3.4 The TF-affine transformations; 3.5 The Prolate Chirplet; 3.6 The TF-affine chirplet space; 3.7 The Gaussian Chirplet; 4 The Projective Chirplet; 5 Extensions to Higher Dimensions; 5.1 Projective Geometry; 6 Applications in Higher Dimensions: Dusting and CEMENT; 6.1 Limitations; 7 Conclusions |
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4 Digital Inscribable Quadrilaterals and Digital Circles5 Implementation; 5.1 Recognition Problem; 5.2 Approximation Problem; 5.3 Segmentation Problem; 6 Conclusions; Appendix; References; Model-based Synthesis of Vision Routines; 1 Introduction; 2 Related Work; 3 FIGURE - Architecture and Control; 4 Model Object Base; 5 Evidence Features; 6 Relations between Objects; 7 Generic Model; 8 Configuration Module; 9 Instances; 10 Experimental Results; 11 Conclusion; Acknowledgements; References; Wavelets and ""Chirplets"": Time-Frequency ''Perspectives"" With Applications |
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A2. Electrostatic with charges: Poisson's equation |
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AcknowledgementsReferences; Electromagnetic Models for Perceptual Grouping; 1 Introduction; 1.1 Low-level perceptual grouping; 1.2 Proximity and directionality; 1.3 Why determining directionality?; 2 Electromagnetic models; 2.1 Motivations; 2.2 Two possible models; 2.3 Poisson model: proximity grouping; 2.4 Poisson model: directional grouping; 3 Implementation, results and discussion; 3.1 Implementation and results; 3.2 Discussion; 4 Conclusion; Acknowledgements; Appendix: Fundamentals of Maxwell's Equations; A1 . Electrostatic and magnetostatic case |
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ReferencesBoundary Feature Extraction and Structural Verification of Objects; 1 Introduction; 2 Feature Extraction by Curvature; 2.1 Dominant Features; 2.2 Curvature Estimation; 2.3 Extreme-Point Detection; 2.4 Knot-Point Detection; 3 Object-Structure Verification; 3.1 Rectangular Shapes; 3.2 Circular Shapes; 3.3 Objects Composed of Lines and Circular Arcs; 4 Conclusions; Acknowledgements; References; Appendix. Derivation of Eq.(4) and Eq.(5); On Circles and Circular Arcs Recognition; 1 Introduction; 2 Schemes for Digitizing Planar Curves; 3 Conditions for Digital Images of Circles |
| Notes |
Description based upon print version of record |
| Bibliography |
Includes bibliographical references |
| Notes |
English |
| Subject |
Computer vision.
|
| Author |
Archibald, Colin.
|
|
Petriu, Emil.
|
| LC no. |
92019672 |
| ISBN |
9810209762 |
|
