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Epipolar Geometry in Stereo, Motion and Object Recognition

A Unified Approach

  • Book
  • © 1996

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Authors:
  1. Gang Xu

    1. Department of Computer Science, Ritsumeikan University, Kusatsu, Japan

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  2. Zhengyou Zhang

    1. INRIA Sophia-Antipolis, Sophia-Antipolis, France

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    You can also search for this author in PubMed   Google Scholar

Part of the book series: Computational Imaging and Vision (CIVI, volume 6)

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Table of contents (9 chapters)

  1. Front Matter

    Pages i-xix
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  2. Introduction

    • Gang Xu, Zhengyou Zhang
    Pages 1-6

  3. Camera Models and Epipolar Geometry

    • Gang Xu, Zhengyou Zhang
    Pages 7-78

  4. Recovery of Epipolar Geometry from Points

    • Gang Xu, Zhengyou Zhang
    Pages 79-166

  5. Recovery of Epipolar Geometry from Line Segments or Straight Lines

    • Gang Xu, Zhengyou Zhang
    Pages 167-204

  6. Redefining Stereo, Motion and Object Recognition Via Epipolar Geometry

    • Gang Xu, Zhengyou Zhang
    Pages 205-219

  7. Image Matching and Uncalibrated Stereo

    • Gang Xu, Zhengyou Zhang
    Pages 221-245

  8. Multiple Rigid Motions: Correspondence and Segmentation

    • Gang Xu, Zhengyou Zhang
    Pages 247-267

  9. 3D Object Recognition and Localization with Model Views

    • Gang Xu, Zhengyou Zhang
    Pages 269-289

  10. Concluding Remarks

    • Gang Xu, Zhengyou Zhang
    Pages 291-292

  11. Back Matter

    Pages 293-315
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About this book

Appendix 164 3. A 3. A. 1 Approximate Estimation of Fundamental Matrix from General Matrix 164 3. A. 2 Estimation of Affine Transformation 165 4 RECOVERY OF EPIPOLAR GEOMETRY FROM LINE SEGMENTS OR LINES 167 Line Segments or Straight Lines 168 4. 1 4. 2 Solving Motion Using Line Segments Between Two Views 173 4. 2. 1 Overlap of Two Corresponding Line Segments 173 Estimating Motion by Maximizing Overlap 175 4. 2. 2 Implementation Details 4. 2. 3 176 Reconstructing 3D Line Segments 4. 2. 4 179 4. 2. 5 Experimental Results 180 4. 2. 6 Discussions 192 4. 3 Determining Epipolar Geometry of Three Views 194 4. 3. 1 Trifocal Constraints for Point Matches 194 4. 3. 2 Trifocal Constraints for Line Correspondences 199 4. 3. 3 Linear Estimation of K, L, and M Using Points and Lines 200 4. 3. 4 Determining Camera Projection Matrices 201 4. 3. 5 Image Transfer 203 4. 4 Summary 204 5 REDEFINING STEREO, MOTION AND OBJECT RECOGNITION VIA EPIPOLAR GEOMETRY 205 5. 1 Conventional Approaches to Stereo, Motion and Object Recognition 205 5. 1. 1 Stereo 205 5. 1. 2 Motion 206 5. 1. 3 Object Recognition 207 5. 2 Correspondence in Stereo, Motion and Object Recognition as 1D Search 209 5. 2. 1 Stereo Matching 209 xi Contents 5. 2. 2 Motion Correspondence and Segmentation 209 5. 2. 3 3D Object Recognition and Localization 210 Disparity and Spatial Disparity Space 210 5.

Authors and Affiliations

  • Department of Computer Science, Ritsumeikan University, Kusatsu, Japan

    Gang Xu

  • INRIA Sophia-Antipolis, Sophia-Antipolis, France

    Zhengyou Zhang

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