About: Chessboard detection

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Chessboards arise frequently in computer vision theory and practice because their highly structured geometry is well-suited for algorithmic detection and processing. The appearance of chessboards in computer vision can be divided into two main areas: camera calibration and feature extraction. This article provides a unified discussion of the role that chessboards play in the canonical methods from these two areas, including references to the seminal literature, examples, and pointers to software implementations.

Attributes	Values
rdfs:label	Chessboard detection (en)
rdfs:comment	Chessboards arise frequently in computer vision theory and practice because their highly structured geometry is well-suited for algorithmic detection and processing. The appearance of chessboards in computer vision can be divided into two main areas: camera calibration and feature extraction. This article provides a unified discussion of the role that chessboards play in the canonical methods from these two areas, including references to the seminal literature, examples, and pointers to software implementations. (en)
foaf:depiction
dcterms:subject	Feature detection (computer vision)
Wikipage page ID	44589207 (xsd:integer)
Wikipage revision ID	992840436 (xsd:integer)
Link from a Wikipage to another Wikipage	Projective geometry Projective space Detection Pinhole camera Maxima and minima Normal (geometry) Interest point detection Pinhole camera model Eigenvalues and eigenvectors Corner detection MATLAB Computer vision Feature (computer vision) Feature extraction Hough transform Numerical stability 3D projection 3D reconstruction from multiple images Feature detection (computer vision) Dimensionality reduction Direct linear transformation Feature detection (computer vision) Photogrammetry Polar coordinate system Camera auto-calibration Camera resectioning Canny edge detector Structure tensor System of linear equations
Link from a Wikipage to an external page	http://www.vision.caltech.edu/bouguetj/calib_doc/htmls/example.html https://github.com/dkogan/mrgingham/ http://www.mathworks.com/help/images/hough-transform.html http://www.mathworks.com/help/images/ref/corner.html http://www.mathworks.com/help/vision/ref/detectcheckerboardpoints.html http://www.mathworks.com/products/computer-vision/ http://www.mathworks.com/products/image/ http://docs.opencv.org/doc/tutorials/calib3d/camera_calibration_square_chess/camera_calibration_square_chess.html http://docs.opencv.org/doc/tutorials/features2d/trackingmotion/harris_detector/harris_detector.html http://docs.opencv.org/doc/tutorials/imgproc/imgtrans/hough_lines/hough_lines.html http://docs.opencv.org/modules/calib3d/doc/camera_calibration_and_3d_reconstruction.html http://www.vision.caltech.edu/bouguetj/calib_doc/
sameAs	Chessboard detection Chessboard detection Chessboard detection
text align	center (en)
dbp:wikiPageUsesTemplate	dbt:Multiple_image dbt:Orphan dbt:FeatureDetectionCompVisNavbox
thumbnail	wiki-commons:Special:FilePath/Chessboard_calibration_setup.png?width=300
align	center (en)
caption	3 (xsd:integer) (en) Canny edge detector applied to chessboard image (en) Output of Harris corner detector (en) Perspective-transformed chessboard image (en) Reconstructed orientations (en) Hough transform of edge image with 19 largest local maxima denoted (en) Lines parameterized by Hough transform local maxima (en) Multiple views of a chessboard for multiplane calibration (en)
height	384 (xsd:integer) 471 (xsd:integer) 548 (xsd:integer) 678 (xsd:integer) 728 (xsd:integer)
image	Chessboard calibration setup.png (en) Harris corners detected on chessboard.png (en) Multiple chessboard views.png (en) Perspective chessboard detected lines.png (en) Perspective chessboard edges.png (en) Perspective chessboard hough transform.png (en) Perspective chessboard.png (en) Reconstructed boards camera.png (en) Reconstructed boards world.png (en)
title	Example: calibration rig (en) Example: corner detection (en) Example: line detection (en) Example: multiplane calibration (en)
total width	300 (xsd:integer) 600 (xsd:integer) 900 (xsd:integer) 1000 (xsd:integer)
width	507 (xsd:integer) 529 (xsd:integer) 681 (xsd:integer)

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