Computer Vision with OpenCV

9.

Camera Calibration and 3D Vision

9.1.

9.1.1.

Pinhole Camera Model

9.1.2.

Camera Matrix Parameters

9.1.3.

Distortion Models

9.1.3.1.

Radial Distortion

9.1.3.2.

Tangential Distortion

9.2.

Camera Calibration Process

9.2.1.

Calibration Pattern Detection

9.2.1.1.

Chessboard Patterns

9.2.1.2.

Circle Grid Patterns

9.2.1.3.

Asymmetric Circle Patterns

9.2.2.

Calibration Computation

9.2.2.1.

Intrinsic Parameters

9.2.2.2.

Extrinsic Parameters

9.2.2.3.

Reprojection Error Analysis

9.2.3.

Image Undistortion

9.2.3.1.

Distortion Correction

9.2.3.2.

Optimal Camera Matrix

9.3.

Pose Estimation

9.3.1.

9.3.2.

SolvePnP Algorithms

9.3.2.1.

Iterative Method

9.3.2.2.

9.3.2.3.

9.3.3.

Pose Refinement

9.4.

9.4.1.

Stereo Camera Setup

9.4.2.

Stereo Calibration

9.4.2.1.

Rectification Process

9.4.2.2.

Fundamental Matrix

9.4.2.3.

Essential Matrix

9.4.3.

Depth Estimation

9.4.3.1.

Stereo Correspondence

9.4.3.2.

Block Matching Algorithm

9.4.3.3.

Semi-Global Block Matching

9.4.3.4.

Disparity Map Generation

9.4.3.5.

Depth Map Conversion

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8. Advanced Image Processing

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10. Deep Learning Integration