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dc.contributor.authorElmahmudi, Ali A.M.
dc.contributor.authorUgail, Hassan
dc.date.accessioned2022-03-20T06:14:24Z
dc.date.accessioned2022-04-20T12:58:47Z
dc.date.available2022-03-20T06:14:24Z
dc.date.available2022-04-20T12:58:47Z
dc.date.issued2021-07
dc.identifier.citationElmahmudi AAM and Ugail H (2020) A framework for facial age progression and regression using exemplar face templates. Visual Computer. 37: 2023-2038.en_US
dc.identifier.urihttp://hdl.handle.net/10454/18903
dc.descriptionYesen_US
dc.description.abstractTechniques for facial age progression and regression have many applications and a myriad of challenges. As such, automatic aged or de-aged face generation has become an important subject of study in recent times. Over the past decade or so, researchers have been working on developing face processing mechanisms to tackle the challenge of generating realistic aged faces for applications related to smart systems. In this paper, we propose a novel approach to try and address this problem. We use template faces based on the formulation of an average face of a given ethnicity and for a given age. Thus, given a face image, the target aged image for that face is generated by applying it to the relevant template face image. The resulting image is controlled by two parameters corresponding to the texture and the shape of the face. To validate our approach, we compute the similarity between aged images and the corresponding ground truth via face recognition. To do this, we have utilised a pre-trained convolutional neural network based on the VGG-face model for feature extraction, and we then use well-known classifiers to compare the features. We have utilised two datasets, namely the FEI and the Morph II, to test, verify and validate our approach. Our experimental results do suggest that the proposed approach achieves accuracy, efficiency and possess flexibility when it comes to facial age progression or regression.en_US
dc.language.isoenen_US
dc.relation.isreferencedbyhttps://doi.org/10.1007/s00371-020-01960-zen_US
dc.rights(c) 2021 The Authors. This is an Open Access article distributed under the Creative Commons CC-BY license (http://creativecommons.org/licenses/by/4.0/)en_US
dc.subjectAge progressionen_US
dc.subjectRegressionen_US
dc.subjectAverage faceen_US
dc.subjectFace similarityen_US
dc.subjectTemplate-based face generationen_US
dc.titleA framework for facial age progression and regression using exemplar face templatesen_US
dc.status.refereedYesen_US
dc.date.Accepted2020
dc.date.application2020-08-17
dc.typeArticleen_US
dc.type.versionPublished versionen_US
dc.rights.licenseCC-BYen_US
dc.date.updated2022-03-20T06:14:25Z
refterms.dateFOA2022-04-20T12:59:10Z
dc.openaccess.statusopenAccessen_US


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