{"corpus_id":26286007,"paper_sha":"8cac2a1331c4f571d7bcbd51cd628d544f5e44f8","doi":"10.1109/ICIP.2002.1038016","arxiv_id":null,"pmid":null,"pmcid":null,"mag_id":2137282724,"dblp_id":"conf/icip/PhungBC02","acl_id":null,"title":"A novel skin color model in YCbCr color space and its application to human face detection","year":2002,"publication_date":"2002-12-10","venue":"Proceedings. International Conference on Image Processing","journal":{"name":"Proceedings. International Conference on Image Processing","pages":"I-I","volume":"1"},"journal_issn":null,"journal_title":null,"publication_types":["JournalArticle","Conference"],"pubmed_pub_types":null,"s2_fields_of_study":["Mathematics","Computer Science"],"reference_count":14,"citation_count":310,"influential_citation_count":9,"is_open_access":false,"arxiv_categories":null,"arxiv_license":null,"arxiv_journal_ref":null,"mesh_headings":null,"chemicals":null,"comments_corrections":null,"source_flags":1,"s2_open_access_pdf_url":null,"s2_open_access_landing_url":null,"s2_open_access_license":null,"s2_open_access_status":null,"pmc_open_access_pdf_url":null,"pmc_open_access_landing_url":null,"pmc_open_access_license":null,"pmc_open_access_status":null,"unpaywall_open_access_pdf_url":null,"unpaywall_open_access_landing_url":null,"unpaywall_open_access_license":null,"unpaywall_open_access_status":null,"abstract":"This paper presents a new human skin color model in YCbCr color space and its application to human face detection. Skin colors are modeled by a set of three Gaussian clusters, each of which is characterized by a centroid and a covariance matrix. The centroids and covariance matrices are estimated from large set of training samples after a k-means clustering process. Pixels in a color input image can be classified into skin or non-skin based on the Mahalanobis distances to the three clusters. Efficient post-processing techniques namely noise removal, shape criteria, elliptic curve fitting and face/non-face classification are proposed in order to further refine skin segmentation results for the purpose of face detection.","claims":[{"public_id":"cl_343bdb85628606258443e5e9ab58840f","status":"active","text":"Centroids and covariance matrices are estimated from a large set of training samples after k-means clustering.","confidence":0.96,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous (12632b8b5f)","roles":["extraction"],"url":"https://sah.borca.ai/u/12632b8b5f"}],"url":"https://sah.borca.ai/claims/cl_343bdb85628606258443e5e9ab58840f"},{"public_id":"cl_1cc9cf1e68f4031933bbe9f0cfab0d0d","status":"active","text":"Noise removal, shape criteria, elliptic curve fitting, and face/non-face classification are proposed to refine skin segmentation for face detection.","confidence":0.97,"contributors":[{"id":1,"public_id":"12632b8b5f","public_label":"Anonymous 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