{"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/nasal-patches-and-curves-for-expression","title":"Nasal Patches and Curves for Expression-robust 3D Face Recognition","arxiv_id":"1901.00206","date":"2019-01-01","proceeding":null,"authors":["Mehryar Emambakhsh","Adrian Evans"],"abstract":"The potential of the nasal region for expression robust 3D face recognition\nis thoroughly investigated by a novel five-step algorithm. First, the nose tip\nlocation is coarsely detected and the face is segmented, aligned and the nasal\nregion cropped. Then, a very accurate and consistent nasal landmarking\nalgorithm detects seven keypoints on the nasal region. In the third step, a\nfeature extraction algorithm based on the surface normals of Gabor-wavelet\nfiltered depth maps is utilised and, then, a set of spherical patches and\ncurves are localised over the nasal region to provide the feature descriptors.\nThe last step applies a genetic algorithm-based feature selector to detect the\nmost stable patches and curves over different facial expressions. The algorithm\nprovides the highest reported nasal region-based recognition ranks on the FRGC,\nBosphorus and BU-3DFE datasets. The results are comparable with, and in many\ncases better than, many state-of-the-art 3D face recognition algorithms, which\nuse the whole facial domain. The proposed method does not rely on sophisticated\nalignment or denoising steps, is very robust when only one sample per subject\nis used in the gallery, and does not require a training step for the\nlandmarking algorithm. https://github.com/mehryaragha/NoseBiometrics","url_abs":"http://arxiv.org/abs/1901.00206v1","url_pdf":"http://arxiv.org/pdf/1901.00206v1.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":"nasal-patches-and-curves-for-expression","repo_url":"https://github.com/mehryaragha/NoseBiometrics","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"denoising","task_name":"Denoising"},{"task_slug":"face-recognition","task_name":"Face Recognition"}],"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}