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With camera resolution ever increasing and the need to rapidly recalibraterobotic platforms in less than ideal environments, there is a need for fasterand more robust chessboard fiducial marker detectors. A new chessboard detectoris proposed that is specifically designed for: high resolution images,focus/motion blur, harsh lighting conditions, and background clutter. This isaccomplished using a new x-corner detector, where for the first time blur isestimated and used in a novel way to enhance corner localization, edgevalidation, and connectivity. Performance is measured and compared againstother libraries using a diverse set of images created by combining multiplethird party datasets and including new specially crafted scenarios designed tostress the state-of-the-art. The proposed detector has the best F1- Score of0.97, runs 1.9x faster than next fastest, and is a top performer for corneraccuracy, while being the only detector to have consistent good performance inall scenarios.

Pyramidal Blur Aware X-Corner Chessboard Detector