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- W2014124367 abstract "Development of autonomic chess-playing robots creates several interesting computer vision problems, including plane calibration and object recognition. Various solutions have been attempted, but most either require a modified chess set or place unreasonable constraints on board conditions and camera angles. A more general solution uses computer vision to automatically determine arbitrary chessboard location and identify chessmen on a standard, unmodified chess set. Although much work has been devoted to probabilistic image recognition in general, this paper presents a novel solution to the specific chessboard location problem that is accurate, less restrictive, and relatively time efficient." @default.
- W2014124367 created "2016-06-24" @default.
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- W2014124367 date "2010-08-01" @default.
- W2014124367 modified "2023-10-16" @default.
- W2014124367 title "Probabilistic location of a populated chessboard using computer vision" @default.
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- W2014124367 doi "https://doi.org/10.1109/mwscas.2010.5548901" @default.
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