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    A framework for facial age progression and regression using exemplar face templates

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    elmahmudi_and_ugail_2021 (3.810Mb)
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    Publication date
    2021-07
    Author
    Elmahmudi, Ali A.M.
    Ugail, Hassan
    Keyword
    Age progression
    Regression
    Average face
    Face similarity
    Template-based face generation
    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/)
    Peer-Reviewed
    Yes
    Open Access status
    openAccess
    
    Metadata
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    Abstract
    Techniques 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.
    URI
    http://hdl.handle.net/10454/18903
    Version
    Published version
    Citation
    Elmahmudi AAM and Ugail H (2020) A framework for facial age progression and regression using exemplar face templates. Visual Computer. 37: 2023-2038.
    Link to publisher’s version
    https://doi.org/10.1007/s00371-020-01960-z
    Type
    Article
    Collections
    Engineering and Informatics Publications

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