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* Update linux_install.markdown Grammar improvements, fixed typos. * Update tutorials.markdown Improvements in grammar. * Update table_of_content_calib3d.markdown * Update camera_calibration_square_chess.markdown Improvements in grammar. Added answer. * Update tutorials.markdown * Update erosion_dilatation.markdown * Update table_of_content_imgproc.markdown * Update warp_affine.markdown * Update camera_calibration_square_chess.markdown Removed extra space. * Update gpu_basics_similarity.markdown Grammatical improvements, fixed typos. * Update trackbar.markdown Improvement for better understanding.
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Camera calibration and 3D reconstruction (calib3d module)
Although we get most of our images in a 2D format they do come from a 3D world. Here you will learn how to find out 3D world information from 2D images.
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@subpage tutorial_camera_calibration_square_chess
Compatibility: > OpenCV 2.0
Author: Victor Eruhimov
You will use some chessboard images to calibrate your camera.
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@subpage tutorial_camera_calibration
Compatibility: > OpenCV 2.0
Author: Bernát Gábor
Camera calibration by using either the chessboard, circle or the asymmetrical circle pattern. Get the images either from a camera attached, a video file or from an image collection.
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@subpage tutorial_real_time_pose
Compatibility: > OpenCV 2.0
Author: Edgar Riba
Real time pose estimation of a textured object using ORB features, FlannBased matcher, PnP approach plus Ransac and Linear Kalman Filter to reject possible bad poses.
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@subpage tutorial_interactive_calibration
Compatibility: > OpenCV 3.1
Author: Vladislav Sovrasov
Camera calibration by using either the chessboard, chAruco, asymmetrical circle or dual asymmetrical circle pattern. Calibration process is continious, so you can see results after each new pattern shot. As an output you get average reprojection error, intrinsic camera parameters, distortion coefficients and confidence intervals for all of evaluated variables.