Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0167-8655(02)00215-5
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dc.titleModel-based varying pose face detection and facial feature registration in colour images
dc.contributor.authorFan, L.
dc.contributor.authorSung, K.-K.
dc.date.accessioned2013-07-04T07:31:48Z
dc.date.available2013-07-04T07:31:48Z
dc.date.issued2003
dc.identifier.citationFan, L., Sung, K.-K. (2003). Model-based varying pose face detection and facial feature registration in colour images. Pattern Recognition Letters 24 (1-3) : 237-249. ScholarBank@NUS Repository. https://doi.org/10.1016/S0167-8655(02)00215-5
dc.identifier.issn01678655
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/39005
dc.description.abstractThis paper presents a hybrid method for varying pose face detection and facial feature registration from colour images. At the first stage, we use a skin-colour Gaussian model to identify possible varying pose face regions. At the second stage, we compare each face candidates with a varying pose face model using a combined feature-texture similarity measure (FTSM). False detections from the first stage are eliminated by setting an appropriate FTSM threshold. Also, one can register the facial features (eyes, nose and mouth) by aligning a prototype face with the unknown pose faces. Experimental results show that the proposed method can achieve reliable face detection and feature registration under various conditions, including different poses, face appearances, and lighting conditions. © 2002 Elsevier Science B.V. All rights reserved.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S0167-8655(02)00215-5
dc.sourceScopus
dc.subjectFace registration
dc.subjectImage matching
dc.subjectSimilarity measure
dc.subjectStatistical modeling
dc.subjectVarying pose face detection
dc.typeArticle
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.doi10.1016/S0167-8655(02)00215-5
dc.description.sourcetitlePattern Recognition Letters
dc.description.volume24
dc.description.issue1-3
dc.description.page237-249
dc.identifier.isiut000180105400022
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