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00:00:00
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Lecture 18: Camera Calibration & 3D Reconstruction |
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00:00:55
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Course Outline |
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00:01:32
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Recap: What Is Stereo Vision? |
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00:02:03
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Recap: Depth with Stereo - Basic Idea |
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00:03:27
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Recap: Epipolar Geometry |
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00:05:32
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Recap: Stereo Geometry With Calibrated Cameras |
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00:08:28
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Recap: Essential Matrix |
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00:11:22
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Recap: Essential Matrix and Epipolar Lines |
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00:12:16
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Recap: Stereo Image Rectification |
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00:15:29
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Recap: Stereo Reconstruction |
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00:16:12
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Correspondence Problem |
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00:16:57
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Dense Correspondence Search |
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00:19:13
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Example: Window Search |
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00:23:13
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Effect of Window Size |
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00:24:52
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Alternative: Sparse Correspondence Search |
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00:27:28
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Dense vs. Sparse |
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00:30:43
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Difficulties in Similarity Constraint |
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00:31:27
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Possible Sources of Error? |
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00:32:17
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Summary: Stereo Reconstruction |
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00:34:23
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Recap: A General Point (SVD) |
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00:35:49
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Topics of This Lecture |
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00:36:08
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Recall: Pinhole Camera Model |
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00:39:53
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Pinhole Camera Model |
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00:41:15
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Camera Coordinate System |
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00:42:22
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Principal Point Offset |
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00:45:13
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Pixel Coordinates: Non-Square Pixels |
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00:46:50
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Camera Rotation and Translation |
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00:51:10
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Summary: Camera Parameters |
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00:57:00
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Camera Parameters: Degrees of Freedom |
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01:03:11
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Calibrating a Camera |
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01:04:15
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Camera Calibration |
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01:05:08
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Camera Calibration: Obtaining the Points |
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01:08:59
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Camera Calibration: DLT Algorithm |
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01:16:30
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Camera Calibration |
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01:17:01
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Camera Calibration: Some Practical Tips |
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01:20:16
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Topics of This Lecture |
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01:20:27
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Two-View Geometry |
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01:22:03
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Revisiting Triangulation |
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01:23:53
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Triangulation: 1) Geometric Approach |
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01:25:04
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Triangulation: 2) Linear Algebraic Approach |
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01:28:25
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Triangulation: 3) Nonlinear Approach |
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01:31:29
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References and Further Reading |