distCoeffs – Input vector of distortion coefficients of 4, 5, or 8 elements.imagePoints – Array of corresponding image points, 2xN/Nx2 1-channel or 1xN/Nx1 2-channel, where N is the number of points.objectPoints – Array of object points in the object coordinate space, 3xN/Nx3 1-channel or 1xN/Nx1 3-channel, where N is the number of points.FindExtrinsicCameraParams2 (objectPoints, imagePoints, cameraMatrix, distCoeffs, rvec, tvec, useExtrinsicGuess=0 ) → None ¶ Parameters: solvePnP (objectPoints, imagePoints, cameraMatrix, distCoeffs ] ] ] ) → retval, rvec, tvec ¶ C: void cvFindExtrinsicCameraParams2 (const CvMat* object_points, const CvMat* image_points, const CvMat* camera_matrix, const CvMat* distortion_coeffs, CvMat* rotation_vector, CvMat* translation_vector, int use_extrinsic_guess=0 ) ¶ Python: cv. Get Helios XYZ data bytes and intensity data: void GetHeliosImage(Arena::IDevice* pHeliosDevice, cv::Mat& intensity_image, cv::Mat& xyz_mm) cv::Mat rotation_vector, translation_vector bool success = cv::solvePnP(target_points_3d_mm, target_points_2d_pix, cameraMatrix, distCoeffs, rotation_vector, translation_vector) Ĭ++: bool solvePnP (InputArray objectPoints, InputArray imagePoints, InputArray cameraMatrix, InputArray distCoeffs, OutputArray rvec, OutputArray tvec, bool useExtrinsicGuess=false, int flags=ITERATIVE ) ¶ Python: cv2. These two outputs will be used in the joint Helios-Triton calibration in the following steps. Successfully following the steps of the tutorial and calling the opencv calibrateCamera() function will give a 3×3 matrix of the camera’s intrinsics (variable cameraMatrix) and a 5-element vector of the distortion coefficients (variable distCoeffs). The process is described in detail in this tutorial: ( Opencv camera calibration tutorial) At least 3 images are required but 4 to 8 images are typically used to get a better-quality calibration. Place the target at your application’s working distance and focus the Triton’s lens so that the calibration target is in focus.Ĭalibrating the Triton camera requires grabbing several images of the calibration chart at different positions within the camera’s field of view. We can achieve this by printing a target with a checkerboard pattern or you can download our calibration target here (15kB, PDF, 8.5 x 11 in)īefore calibrating the Triton camera you must focus its lens. Before the data between the two cameras can be combined, we must first calibrate the lens on the Triton color camera to find its optical center and focal length (intrinsics), and lens distortion coefficients (pinhole model).
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