| Introduction / 1： |
| The Problem / 1.1： |
| Applications / 1.1.1： |
| The Computer Graphics Approach / 1.1.2： |
| Avoiding the Model / 1.1.3： |
| A Review of Stereo Vision / 1.2： |
| Camera Model and Image Formation / 1.2.1： |
| Stereo Geometry / 1.2.2： |
| The Correspondence Problem / 1.2.3： |
| The Epipolar Constraint / 1.2.4： |
| A Simple Stereo Geometry / 1.2.5： |
| Rectification / 1.2.6： |
| Example: SSD / 1.2.7： |
| Contributions and Outline / 1.3： |
| A Survey of Image-Based Rendering and Stereo / 2： |
| Image-Based Rendering / 2.1： |
| View Synthesis Based on Stereo / 2.1.1： |
| View Interpolation / 2.1.2： |
| Mosaics and Layered Representations / 2.1.3： |
| Stereo / 2.2： |
| A Framework for Stereo / 2.2.1： |
| Preprocessing / 2.2.2： |
| Matching Cost / 2.2.3： |
| Evidence Aggregation / 2.2.4： |
| Disparity Selection / 2.2.5： |
| Sub-Pixel Disparity Computation / 2.2.6： |
| Diffusion-Based Techniques / 2.2.7： |
| Other Techniques / 2.2.8： |
| Promising Recent Approaches / 2.2.9： |
| Computer Vision Books / 2.3： |
| View Synthesis / 3： |
| Geometry / 3.1： |
| Three-View Rectification / 3.1.1： |
| The Linear Warping Equation / 3.1.2： |
| Computing the Rectifying Homographies / 3.1.3： |
| Synthesizing a New View / 3.2： |
| Resolving Visibility / 3.2.1： |
| Holes and Sampling Gaps / 3.2.2： |
| Combining Information from Both Images / 3.2.3： |
| Adjusting Intensities / 3.2.4： |
| Filling Holes / 3.2.5： |
| The View Synthesis Algorithm / 3.2.6： |
| Limitations of the Approach / 3.2.7： |
| Experiments / 3.3： |
| Image-Based Scene Representations / 3.4： |
| Summary / 3.5： |
| Re-evaluating Stereo / 4： |
| Traditional Applications of Stereo / 4.1： |
| Automated Cartography / 4.1.1： |
| Robot Navigation / 4.1.2： |
| 3D Reconstruction / 4.1.3： |
| 3D Recognition / 4.1.4： |
| Visual Servoing / 4.1.5： |
| Full vs. Weak Calibration / 4.1.6： |
| Comparison of Requirements / 4.1.7： |
| Stereo for View Synthesis / 4.2： |
| Accuracy / 4.3： |
| Correct vs. Realistic Views / 4.4： |
| Areas of Uniform Intensities / 4.5： |
| Geometric Constraints / 4.5.1： |
| Interpolated Views / 4.5.2： |
| Extrapolated Views / 4.5.3： |
| General Views and the Aperture Problem / 4.5.4： |
| Assigning Canonical Depth Interpretations / 4.5.5： |
| Does Adding More Cameras Help? / 4.5.6： |
| Partial Occlusion / 4.6： |
| Gradient-Based Stereo / 4.7： |
| Similarity and Confidence / 5.1： |
| Displacement-Oriented Stereo / 5.2： |
| The Evidence Measure / 5.3： |
| Comparing Two Gradient Vectors / 5.3.1： |
| Comparing Gradient Fields / 5.3.2： |
| Computing Gradients of Discrete Images / 5.3.3： |
| Accumulating the Measure / 5.4： |
| Stereo: 1D Search Range / 5.5： |
| General Motion: 2D Search Range / 5.5.3： |
| Computing Disparity Maps for View Synthesis / 5.6： |
| Occlusion Boundaries / 5.6.1： |
| Detecting Partially Occluded Points and Uniform Regions / 5.6.2： |
| Extrapolating the Disparities / 5.6.3： |
| Efficiency / 5.7： |
| Discussion and Possible Extensions / 5.8： |
| Stereo Using Diffusion / 5.9： |
| Disparity Space / 6.1： |
| The SSD Algorithm and Boundary Blurring / 6.2： |
| Aggregating Support by Diffusion / 6.3： |
| The Membrane Model / 6.3.1： |
| Support Function for the Membrane Model / 6.3.2： |
| Diffusion with Local Stopping / 6.4： |
| A Bayesian Model of Stereo Matching / 6.5： |
| The Prior Model / 6.5.1： |
| The Measurement Model / 6.5.2： |
| Explicit Local Distribution Model / 6.5.3： |
| Conclusion / 6.6： |
| Contributions in View Synthesis / 7.1： |
| Contributions in Stereo / 7.2： |
| Extensions and Future Work / 7.3： |
| Bibliography |
図書
ＥＢ
