Chessboards[[Chessboard]]s 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 resectioning|camera calibration]] and [[Feature (computer vision)|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.
