{"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/fast-localization-of-facial-landmark-points","title":"Fast Localization of Facial Landmark Points","arxiv_id":"1403.6888","date":"2014-03-26","proceeding":null,"authors":["Nenad Markuš","Miroslav Frljak","Igor S. Pandžić","Jörgen Ahlberg","Robert Forchheimer"],"abstract":"Localization of salient facial landmark points, such as eye corners or the\ntip of the nose, is still considered a challenging computer vision problem\ndespite recent efforts. This is especially evident in unconstrained\nenvironments, i.e., in the presence of background clutter and large head pose\nvariations. Most methods that achieve state-of-the-art accuracy are slow, and,\nthus, have limited applications. We describe a method that can accurately\nestimate the positions of relevant facial landmarks in real-time even on\nhardware with limited processing power, such as mobile devices. This is\nachieved with a sequence of estimators based on ensembles of regression trees.\nThe trees use simple pixel intensity comparisons in their internal nodes and\nthis makes them able to process image regions very fast. We test the developed\nsystem on several publicly available datasets and analyse its processing speed\non various devices. Experimental results show that our method has practical\nvalue.","url_abs":"http://arxiv.org/abs/1403.6888v2","url_pdf":"http://arxiv.org/pdf/1403.6888v2.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":"fast-localization-of-facial-landmark-points","repo_url":"https://github.com/Suaro/pidroid","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null},{"paper_slug":"fast-localization-of-facial-landmark-points","repo_url":"https://github.com/esimov/pigo","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"fast-localization-of-facial-landmark-points","repo_url":"https://github.com/hggym/pigo","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"facial-landmark-detection","task_name":"Facial Landmark Detection"}],"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}