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1 | (4) |
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2 Optical Flow Estimation |
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5 | (30) |
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2.1 Optical Flow and Optical Aperture |
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5 | (2) |
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2.2 Feature-Based Optical Flow Approaches |
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7 | (4) |
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2.2.1 Census Based Optical Flow |
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8 | (2) |
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2.2.2 The Optical Flow Constraint |
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10 | (1) |
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2.2.3 Lucas-Kanade Method |
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10 | (1) |
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11 | (6) |
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2.3.1 Total Variation Optical Flow |
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13 | (1) |
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2.3.2 Quadratic Relaxation |
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14 | (1) |
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2.3.3 Large Displacement Flow: Novel Algorithmic Approaches |
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15 | (2) |
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2.3.4 Other Optical Flow Approaches |
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17 | (1) |
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2.4 The Flow Refinement Framework |
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17 | (18) |
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2.4.1 Data Term Optimization |
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18 | (6) |
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2.4.2 Smoothness Term Evaluation |
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24 | (6) |
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2.4.3 Implementation Details |
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30 | (5) |
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3 Residual Images and Optical Flow Results |
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35 | (16) |
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3.1 Increasing Robustness to Illumination Changes |
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35 | (3) |
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3.2 Quantitative Evaluation of the Refinement Optical Flow |
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38 | (7) |
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38 | (4) |
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42 | (2) |
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44 | (1) |
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3.3 Results for Traffic Scenes |
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45 | (3) |
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48 | (3) |
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51 | (14) |
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51 | (4) |
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53 | (1) |
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4.1.2 A Decoupled Approach for Scene Flow |
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53 | (2) |
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4.2 Formulation and Solving of the Constraint Equations |
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55 | (6) |
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55 | (2) |
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4.2.2 Scene Flow Motion Constraints |
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57 | (2) |
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4.2.3 Solving the Scene Flow Equations |
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59 | (1) |
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4.2.4 Evaluation with Different Stereo Inputs |
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59 | (2) |
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4.3 From Image Scene Flow to 3D World Scene Flow |
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61 | (4) |
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5 Motion Metrics for Scene Flow |
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65 | (16) |
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5.1 Ground Truth vs. Reality |
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65 | (1) |
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5.2 Derivation of a Pixel-Wise Accuracy Measure |
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66 | (9) |
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5.2.1 A Quality Measure for the Disparity |
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67 | (6) |
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5.2.2 A Quality Measure for the Scene Flow |
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73 | (1) |
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5.2.3 Estimating Scene Flow Standard Deviations |
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74 | (1) |
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5.3 Residual Motion Likelihood |
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75 | (2) |
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77 | (4) |
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6 Extensions of Scene Flow |
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81 | (18) |
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6.1 Flow Cut-Moving Object Segmentation |
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81 | (11) |
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6.6.1 Segmentation Algorithm |
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83 | (2) |
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6.1.2 Deriving the Motion Likelihoods |
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85 | (3) |
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6.1.3 Experimental Results and Discussion |
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88 | (4) |
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6.2 Kalman Filters for Scene Flow Vectors |
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92 | (7) |
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6.2.1 Filtered Flow and Stereo: 6D-Vision |
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92 | (2) |
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6.2.2 Filtered Dense Optical Flow and Stereo: Dense-6D |
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94 | (1) |
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6.2.3 Filtered Variational Scene Flow: Variational-6D |
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95 | (1) |
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6.2.4 Evaluation with Ground Truth Information |
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96 | (2) |
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98 | (1) |
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99 | (2) |
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8 Appendix: Data Terms and Quadratic Optimization |
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101 | (10) |
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8.1 Optical Flow Constraint Data Term |
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101 | (1) |
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8.2 Adaptive Fundamental Matrix Constraint |
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101 | (2) |
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8.3 Quadratic Optimization via Thresholding |
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103 | (8) |
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8.3.1 Karush-Kuhn-Tucker (KKT) Conditions |
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103 | (1) |
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104 | (2) |
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106 | (5) |
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9 Appendix: Scene Flow Implementation Using Euler-Lagrange Equations |
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111 | (8) |
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9.1 Minimization of the Scene Flow Energy |
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111 | (2) |
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9.2 Implementation of Scene Flow |
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113 | (6) |
Glossary |
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119 | (2) |
References |
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121 | (6) |
Index |
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127 | |