{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/chess-quick-and-robust-detection-of-chess","title":"ChESS - Quick and Robust Detection of Chess-board Features","arxiv_id":"1301.5491","date":"2013-01-23","proceeding":null,"authors":["Stuart Bennett","Joan Lasenby"],"abstract":"Localization of chess-board vertices is a common task in computer vision,\nunderpinning many applications, but relatively little work focusses on\ndesigning a specific feature detector that is fast, accurate and robust. In\nthis paper the `Chess-board Extraction by Subtraction and Summation' (ChESS)\nfeature detector, designed to exclusively respond to chess-board vertices, is\npresented. The method proposed is robust against noise, poor lighting and poor\ncontrast, requires no prior knowledge of the extent of the chess-board pattern,\nis computationally very efficient, and provides a strength measure of detected\nfeatures. Such a detector has significant application both in the key field of\ncamera calibration, as well as in Structured Light 3D reconstruction. Evidence\nis presented showing its robustness, accuracy, and efficiency in comparison to\nother commonly used detectors both under simulation and in experimental 3D\nreconstruction of flat plate and cylindrical objects","url_abs":"http://arxiv.org/abs/1301.5491v1","url_pdf":"http://arxiv.org/pdf/1301.5491v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"chess-quick-and-robust-detection-of-chess","repo_url":"https://github.com/dkogan/mrgingham","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"3d-reconstruction","task_name":"3D Reconstruction"},{"task_slug":"camera-calibration","task_name":"Camera Calibration"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}