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A computational framework for segmentation and grouping

Author: Gérard Medioni; Mi-Suen Lee; Chi-Keung Tang
Publisher: Amsterdam ; New York : Elsevier, 2000.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:
This book represents a summary of the research we have been conducting since the early 1990s, and describes a conceptual framework which addresses some current shortcomings, and proposes a unified approach for a broad class of problems. While the framework is defined, our research continues, and some of the elements presented here will no doubt evolve in the coming years. It is organized in eight chapters. In the  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Medioni, Gérard.
Computational framework for segmentation and grouping.
Amsterdam ; New York : Elsevier, 2000
(DLC) 00023205
(OCoLC)43481750
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Gérard Medioni; Mi-Suen Lee; Chi-Keung Tang
ISBN: 9780444503534 0444503536 9780080529486 0080529488
OCLC Number: 162578272
Description: 1 online resource (xvi, 260 pages) : illustrations (some color)
Contents: Cover --
Table of Contents --
List of Figures --
Preface --
Acknowledgements --
Chapter 1. Introduction --
1.1 Motivation and Goals --
1.2 Our Approach --
1.3 Overview of the Proposed Method --
1.4 Contribution of this book --
1.5 Notations --
Chapter 2. Previous Work --
2.1 Regularization --
2.2 Consistent Labeling --
2.3 Clustering and Robust Methods --
2.4 Artificial Neural Network Approach --
2.5 Novelty of Our Approach --
Chapter 3. The Salient Feature Inference Engine --
3.1 Overview of the Salient Inference Engine --
3.2 Representation --
3.3 Communication through Tensor Voting --
3.4 Derivation and Properties of the Fundamental Voting Field --
3.5 Implementation of Tensor Voting --
3.6 Feature Extraction --
3.7 Complexity --
3.8 Summary --
Chapter 4. Feature Extraction --
4.1 Extremal Curves in 2-D --
4.2 Extremal Surfaces in 3-D --
4.3 Extremal Curves in 3-D --
4.4 Complexity --
4.5 Summary --
Chapter 5. Feature Inference in 2-D --
5.1 Related work --
5.2 Inference of junctions and curves from oriented data --
5.3 Inference of junctions and curves from non-oriented data --
5.4 Interesting properties --
5.5 End-point grouping --
5.6 Detection of curve end-points and region boundaries --
5.7 Integrated feature extraction in 2-D --
5.8 Applications --
5.9 Summary --
Chapter 6. Feature Inference in 3-D --
6.1 Related Work --
6.2 Feature inference from oriented and non-oriented data --
6.3 Feature inference from oriented data --
6.4 Feature inference from non-oriented data --
6.5 Examples --
6.6 Integrated feature inference in 3-D --
6.7 Experiments --
6.8 Applications --
6.9 Summary --
Chapter 7. Application to Early Vision Problems --
7.1 Shape from Shading --
7.2 Shape from Stereo --
7.3 Accurate Motion Flow Estimation with Discontinuities --
Chapter 8. Conclusion --
8.1 Summary --
8.2 Future Research --
Appendix A: Tensor analysis --
Appendix B: Details of the Marching Algorithms --
Appendix C: Software Systems --
References --
Author Index --
Index --
Color Plate Section --
Last Page.
Responsibility: Gérard Medioni, Mi-Suen Lee, Chi-Keung Tang.
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Abstract:

This summary of the research carried out by the authors over the 1990s describes a conceptual framework which addresses some shortcomings, and proposes a unified approach for a broad class of  Read more...

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