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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. (en)
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- 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)
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- 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)
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- Example: calibration rig (en)
- Example: corner detection (en)
- Example: line detection (en)
- Example: multiplane calibration (en)
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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. (en)
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- Chessboard detection (en)
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