Two Camera Calibration Methods in MATLAB: Zhang's Method and Tsai's Method

As requested, I will modify the text to extend its length while maintaining the core concepts. In MATLAB, there are two primary approaches for camera calibration: Zhang's method and Tsai's method. Zhang's calibration approach primarily utilizes checkerboard patterns for camera parameter estimation, while Tsai's method focuses on determining camera intrinsic and extrinsic parameters through direct measurement and observation. The checkerboard-based method (Zhang's approach) requires placing a specialized calibration board at various positions and orientations while capturing multiple images from different viewpoints. Implementation typically involves using MATLAB's Computer Vision Toolbox functions like detectCheckerboardPoints() to identify corner points and estimateCameraParameters() to calculate camera matrix, distortion coefficients, and extrinsic parameters. The algorithm works by establishing correspondences between 3D world points (checkerboard corners) and their 2D image projections, then solving the camera projection matrix using least squares optimization. In contrast, Tsai's calibration method relies on observing and measuring known points in 3D space. These reference points can be checkerboard corners or other predefined object features with known world coordinates. The implementation involves measuring these points' image positions and their corresponding spatial coordinates, then applying Tsai's algorithm which separates intrinsic and extrinsic parameter estimation. Key steps include radial alignment constraint application and two-stage parameter calculation - first solving for external parameters using direct linear transformation, then refining intrinsic parameters with nonlinear optimization. Both methods ultimately compute camera intrinsic parameters (focal length, principal point, skew coefficient) and extrinsic parameters (rotation matrix, translation vector). Zhang's method is more automated and suitable for structured environments, while Tsai's approach offers flexibility for custom calibration setups. MATLAB provides built-in support for Zhang's method through the Camera Calibrator app and vision toolbox functions, whereas Tsai's implementation often requires custom coding based on the original algorithm specifications. Therefore, as per the requirements, these are the two principal camera calibration methodologies available in MATLAB: Zhang's checkerboard-based approach and Tsai's parameter-based calibration technique, each with distinct implementation strategies and application scenarios.