Automatic eyeglasses removal from face images
In this paper, we present an intelligent image editing and face synthesis system that automatically removes eyeglasses from an input frontal face image. Although conventional image editing tools can be used to remove eyeglasses by pixel-level editing, filling in the deleted eyeglasses region with th...
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Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence 2004-03, Vol.26 (3), p.322-336 |
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creator | Wu, Chenyu Liu, Ce Shum, Heung-Yueng Xu, Ying-Qing Zhang, Zhengyou |
description | In this paper, we present an intelligent image editing and face synthesis system that automatically removes eyeglasses from an input frontal face image. Although conventional image editing tools can be used to remove eyeglasses by pixel-level editing, filling in the deleted eyeglasses region with the right content is a difficult problem. Our approach works at the object level where the eyeglasses are automatically located, removed as one piece, and the void region filled. Our system consists of three parts: eyeglasses detection, eyeglasses localization, and eyeglasses removal. First, an eye region detector, trained offline, is used to approximately locate the region of eyes, thus the region of eyeglasses. A Markov-chain Monte Carlo method is then used to accurately locate key points on the eyeglasses frame by searching for the global optimum of the posterior. Subsequently, a novel sample-based approach is used to synthesize the face image without the eyeglasses. Specifically, we adopt a statistical analysis and synthesis approach to learn the mapping between pairs of face images with and without eyeglasses from a database. Extensive experiments demonstrate that our system effectively removes eyeglasses. |
doi_str_mv | 10.1109/TPAMI.2004.1262319 |
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Although conventional image editing tools can be used to remove eyeglasses by pixel-level editing, filling in the deleted eyeglasses region with the right content is a difficult problem. Our approach works at the object level where the eyeglasses are automatically located, removed as one piece, and the void region filled. Our system consists of three parts: eyeglasses detection, eyeglasses localization, and eyeglasses removal. First, an eye region detector, trained offline, is used to approximately locate the region of eyes, thus the region of eyeglasses. A Markov-chain Monte Carlo method is then used to accurately locate key points on the eyeglasses frame by searching for the global optimum of the posterior. Subsequently, a novel sample-based approach is used to synthesize the face image without the eyeglasses. Specifically, we adopt a statistical analysis and synthesis approach to learn the mapping between pairs of face images with and without eyeglasses from a database. Extensive experiments demonstrate that our system effectively removes eyeglasses.</description><identifier>ISSN: 0162-8828</identifier><identifier>EISSN: 1939-3539</identifier><identifier>DOI: 10.1109/TPAMI.2004.1262319</identifier><identifier>PMID: 15376880</identifier><identifier>CODEN: ITPIDJ</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Algorithms ; Artificial Intelligence ; Computer vision ; Detectors ; Editing ; Eyeglasses ; Eyes ; Face - anatomy & histology ; Face detection ; Female ; Filling ; Humans ; Image databases ; Image Enhancement - methods ; Image Interpretation, Computer-Assisted - methods ; Image resolution ; Information Storage and Retrieval ; Male ; Pattern Recognition, Automated ; Photography - methods ; Pixel ; Reproducibility of Results ; Sensitivity and Specificity ; Signal Processing, Computer-Assisted ; Statistical analysis ; Studies ; Subtraction Technique ; User-Computer Interface</subject><ispartof>IEEE transactions on pattern analysis and machine intelligence, 2004-03, Vol.26 (3), p.322-336</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) 2004</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c421t-3853607f4cdd58c8dd906d96d6e06c62b9a943d0b8cf093f0f41ae0bb41037ca3</citedby><cites>FETCH-LOGICAL-c421t-3853607f4cdd58c8dd906d96d6e06c62b9a943d0b8cf093f0f41ae0bb41037ca3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/1262319$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,776,780,792,27903,27904,54736</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/1262319$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15376880$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wu, Chenyu</creatorcontrib><creatorcontrib>Liu, Ce</creatorcontrib><creatorcontrib>Shum, Heung-Yueng</creatorcontrib><creatorcontrib>Xu, Ying-Qing</creatorcontrib><creatorcontrib>Zhang, Zhengyou</creatorcontrib><title>Automatic eyeglasses removal from face images</title><title>IEEE transactions on pattern analysis and machine intelligence</title><addtitle>TPAMI</addtitle><addtitle>IEEE Trans Pattern Anal Mach Intell</addtitle><description>In this paper, we present an intelligent image editing and face synthesis system that automatically removes eyeglasses from an input frontal face image. Although conventional image editing tools can be used to remove eyeglasses by pixel-level editing, filling in the deleted eyeglasses region with the right content is a difficult problem. Our approach works at the object level where the eyeglasses are automatically located, removed as one piece, and the void region filled. Our system consists of three parts: eyeglasses detection, eyeglasses localization, and eyeglasses removal. First, an eye region detector, trained offline, is used to approximately locate the region of eyes, thus the region of eyeglasses. A Markov-chain Monte Carlo method is then used to accurately locate key points on the eyeglasses frame by searching for the global optimum of the posterior. Subsequently, a novel sample-based approach is used to synthesize the face image without the eyeglasses. Specifically, we adopt a statistical analysis and synthesis approach to learn the mapping between pairs of face images with and without eyeglasses from a database. Extensive experiments demonstrate that our system effectively removes eyeglasses.</description><subject>Algorithms</subject><subject>Artificial Intelligence</subject><subject>Computer vision</subject><subject>Detectors</subject><subject>Editing</subject><subject>Eyeglasses</subject><subject>Eyes</subject><subject>Face - anatomy & histology</subject><subject>Face detection</subject><subject>Female</subject><subject>Filling</subject><subject>Humans</subject><subject>Image databases</subject><subject>Image Enhancement - methods</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Image resolution</subject><subject>Information Storage and Retrieval</subject><subject>Male</subject><subject>Pattern Recognition, Automated</subject><subject>Photography - methods</subject><subject>Pixel</subject><subject>Reproducibility of Results</subject><subject>Sensitivity and Specificity</subject><subject>Signal Processing, Computer-Assisted</subject><subject>Statistical analysis</subject><subject>Studies</subject><subject>Subtraction Technique</subject><subject>User-Computer Interface</subject><issn>0162-8828</issn><issn>1939-3539</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2004</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNqFkMtKw0AUhgdRbK2-gIIEF-5Sz1wynVmW4qVQ0UVdD5OZk5KSNHWmEfr2pjYguHF1Fuf7z-Uj5JrCmFLQD8v36et8zADEmDLJONUnZEg11ynPuD4lQ6CSpUoxNSAXMa4BqMiAn5MBzfhEKgVDkk7bXVPbXekS3OOqsjFiTALWzZetkiI0dVJYh0lZ2xXGS3JW2CriVV9H5OPpcTl7SRdvz_PZdJE6wegu5SrjEiaFcN5nyinvNUivpZcI0kmWa6sF95ArV4DmBRSCWoQ8FxT4xFk-IvfHudvQfLYYd6Yuo8Oqshts2mhkd7zmHfwfyJSUNOuWjcjdH3DdtGHTPWGUEsAPNjqIHSEXmhgDFmYbusfD3lAwB-XmR7k5KDe98i50209u8xr9b6R33AE3R6BExN92H_8GAPqDVw</recordid><startdate>200403</startdate><enddate>200403</enddate><creator>Wu, Chenyu</creator><creator>Liu, Ce</creator><creator>Shum, Heung-Yueng</creator><creator>Xu, Ying-Qing</creator><creator>Zhang, Zhengyou</creator><general>IEEE</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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Although conventional image editing tools can be used to remove eyeglasses by pixel-level editing, filling in the deleted eyeglasses region with the right content is a difficult problem. Our approach works at the object level where the eyeglasses are automatically located, removed as one piece, and the void region filled. Our system consists of three parts: eyeglasses detection, eyeglasses localization, and eyeglasses removal. First, an eye region detector, trained offline, is used to approximately locate the region of eyes, thus the region of eyeglasses. A Markov-chain Monte Carlo method is then used to accurately locate key points on the eyeglasses frame by searching for the global optimum of the posterior. Subsequently, a novel sample-based approach is used to synthesize the face image without the eyeglasses. Specifically, we adopt a statistical analysis and synthesis approach to learn the mapping between pairs of face images with and without eyeglasses from a database. Extensive experiments demonstrate that our system effectively removes eyeglasses.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>15376880</pmid><doi>10.1109/TPAMI.2004.1262319</doi><tpages>15</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Artificial Intelligence Computer vision Detectors Editing Eyeglasses Eyes Face - anatomy & histology Face detection Female Filling Humans Image databases Image Enhancement - methods Image Interpretation, Computer-Assisted - methods Image resolution Information Storage and Retrieval Male Pattern Recognition, Automated Photography - methods Pixel Reproducibility of Results Sensitivity and Specificity Signal Processing, Computer-Assisted Statistical analysis Studies Subtraction Technique User-Computer Interface |
title | Automatic eyeglasses removal from face images |
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