Glasses removal from facial image using recursive error compensation
In this paper, we propose a new method of removing glasses from a human frontal facial image. We first detect the regions occluded by the glasses and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of...
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| Veröffentlicht in: | IEEE transactions on pattern analysis and machine intelligence 2005-05, Vol.27 (5), p.805-811 |
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| container_title | IEEE transactions on pattern analysis and machine intelligence |
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| creator | Park, Jeong-Seon Oh, You Hwa Ahn, Sang Chul Lee, Seong-Whan |
| description | In this paper, we propose a new method of removing glasses from a human frontal facial image. We first detect the regions occluded by the glasses and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame or of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion and we believe that this method can also be used to enhance the performance of face recognition systems. |
| doi_str_mv | 10.1109/TPAMI.2005.103 |
| format | Article |
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We first detect the regions occluded by the glasses and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame or of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion and we believe that this method can also be used to enhance the performance of face recognition systems.</description><identifier>ISSN: 0162-8828</identifier><identifier>EISSN: 1939-3539</identifier><identifier>DOI: 10.1109/TPAMI.2005.103</identifier><identifier>PMID: 15875801</identifier><identifier>CODEN: ITPIDJ</identifier><language>eng</language><publisher>Los Alamitos, CA: IEEE</publisher><subject>Algorithms ; Applied sciences ; Artificial Intelligence ; Cluster Analysis ; clustering algorithms ; Computer Graphics ; Computer science; control theory; systems ; EM algorithm ; Error compensation ; Exact sciences and technology ; Eyeglasses ; Eyes ; Face - anatomy & histology ; Face detection ; Face recognition ; Facial ; Feedback ; Glass ; Humans ; Image Enhancement - methods ; Image generation ; Image Interpretation, Computer-Assisted - methods ; Image reconstruction ; Index Terms- Kernel methods ; Information Storage and Retrieval - methods ; K-Means ; Numerical Analysis, Computer-Assisted ; one class SVM ; Pattern analysis ; Pattern Recognition, Automated - methods ; Pattern recognition. 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We first detect the regions occluded by the glasses and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame or of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion and we believe that this method can also be used to enhance the performance of face recognition systems.</description><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Artificial Intelligence</subject><subject>Cluster Analysis</subject><subject>clustering algorithms</subject><subject>Computer Graphics</subject><subject>Computer science; control theory; systems</subject><subject>EM algorithm</subject><subject>Error compensation</subject><subject>Exact sciences and technology</subject><subject>Eyeglasses</subject><subject>Eyes</subject><subject>Face - anatomy & histology</subject><subject>Face detection</subject><subject>Face recognition</subject><subject>Facial</subject><subject>Feedback</subject><subject>Glass</subject><subject>Humans</subject><subject>Image Enhancement - methods</subject><subject>Image generation</subject><subject>Image Interpretation, Computer-Assisted - methods</subject><subject>Image reconstruction</subject><subject>Index Terms- Kernel methods</subject><subject>Information Storage and Retrieval - methods</subject><subject>K-Means</subject><subject>Numerical Analysis, Computer-Assisted</subject><subject>one class SVM</subject><subject>Pattern analysis</subject><subject>Pattern Recognition, Automated - methods</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Principal component analysis</subject><subject>Recursive</subject><subject>Reflection</subject><subject>Reproducibility of Results</subject><subject>Robustness</subject><subject>Sensitivity and Specificity</subject><subject>Shape</subject><subject>Signal Processing, Computer-Assisted</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>2005</creationdate><recordtype>article</recordtype><sourceid>RIE</sourceid><sourceid>EIF</sourceid><recordid>eNqF0c9rFDEUB_Agil2rVy-CDIJ6mvW9ZPLrWKrWQks91POQybyUKTOTNdkp9L836y4seKi5JOR98iDvy9hbhDUi2C-3P8-uL9ccQK4RxDO2QitsLaSwz9kKUPHaGG5O2Kuc7wGwkSBeshOURksDuGJfL0aXM-Uq0RQf3FiFFKcqOD-U8zC5O6qWPMx3pe6XlIcHqiilmCofpw3N2W2HOL9mL4IbM7057Kfs1_dvt-c_6qubi8vzs6vaN0JsaxMaZ0UPkoPpMXRaaI299sL0DThNllvTdV3jwEvfBzABy_LBGocqEIlT9nnfd5Pi74Xytp2G7Gkc3Uxxya2xCrWyShX56UmptEGpuf0v5GVKCMAL_PAPvI9Lmst3W6O00pI3pqD1HvkUc04U2k0qQ0yPLUK7y6v9m1e7y6tcifLg_aHr0k3UH_khoAI-HoDL3o0hudkP-ejU7icCinu3dwMRHcsNaGOE-AMEGqUk</recordid><startdate>20050501</startdate><enddate>20050501</enddate><creator>Park, Jeong-Seon</creator><creator>Oh, You Hwa</creator><creator>Ahn, Sang Chul</creator><creator>Lee, Seong-Whan</creator><general>IEEE</general><general>IEEE Computer Society</general><general>The Institute of Electrical and Electronics Engineers, Inc. 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We first detect the regions occluded by the glasses and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame or of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion and we believe that this method can also be used to enhance the performance of face recognition systems.</abstract><cop>Los Alamitos, CA</cop><pub>IEEE</pub><pmid>15875801</pmid><doi>10.1109/TPAMI.2005.103</doi><tpages>7</tpages></addata></record> |
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| subjects | Algorithms Applied sciences Artificial Intelligence Cluster Analysis clustering algorithms Computer Graphics Computer science control theory systems EM algorithm Error compensation Exact sciences and technology Eyeglasses Eyes Face - anatomy & histology Face detection Face recognition Facial Feedback Glass Humans Image Enhancement - methods Image generation Image Interpretation, Computer-Assisted - methods Image reconstruction Index Terms- Kernel methods Information Storage and Retrieval - methods K-Means Numerical Analysis, Computer-Assisted one class SVM Pattern analysis Pattern Recognition, Automated - methods Pattern recognition. Digital image processing. Computational geometry Principal component analysis Recursive Reflection Reproducibility of Results Robustness Sensitivity and Specificity Shape Signal Processing, Computer-Assisted Subtraction Technique User-Computer Interface |
| title | Glasses removal from facial image using recursive error compensation |
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