{"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/machine-learning-for-realisticball-detection","title":"Machine Learning for RealisticBall Detection in RoboCup SPL","arxiv_id":"1707.03628","date":"2017-07-12","proceeding":null,"authors":["Domenico Bloisi","Francesco Del Duchetto","Tiziano Manoni","Vincenzo Suriani"],"abstract":"In this technical report, we describe the use of a machine learning approach\nfor detecting the realistic black and white ball currently in use in the\nRoboCup Standard Platform League. Our aim is to provide a ready-to-use software\nmodule that can be useful for the RoboCup SPL community. To this end, the\napproach is integrated within the official B-Human code release 2016. The\ncomplete code for the approach presented in this work can be downloaded from\nthe SPQR Team homepage at http://spqr.diag.uniroma1.it and from the SPQR Team\nGitHub repository at https://github.com/SPQRTeam/SPQRBallPerceptor. The\napproach has been tested in multiple environments, both indoor and outdoor.\nFurthermore, the ball detector described in this technical report has been used\nby the SPQR Robot Soccer Team during the competitions of the Robocup German\nOpen 2017. To facilitate the use of our code by other teams, we have prepared a\nstep-by-step installation guide.","url_abs":"http://arxiv.org/abs/1707.03628v1","url_pdf":"http://arxiv.org/pdf/1707.03628v1.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":"machine-learning-for-realisticball-detection","repo_url":"https://github.com/SPQRTeam/SPQRBallPerceptor","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"}],"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}