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 three main areas: camera calibration, feature extraction, and real-world board state recognition (handling occlusions).
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 three main areas: camera calibration, feature extraction, and real-world board state recognition (handling occlusions).
Source: Wikipedia "Chessboard detection" · CC BY-SA 4.0
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