Face reconstruction from image sequences for forensic face comparison

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    The authors explore the possibilities of a dense model-free three-dimensional (3D) face reconstruction method, based on image sequences from a single camera, to improve the current state of forensic face comparison. They propose a new model-free 3D reconstruction method for faces, based on the Lambertian reflectance model to estimate the albedo and to refine the 3D shape of the face. This method avoids any form of bias towards face models and is therefore suitable in a forensic face comparison process. The proposed method can reconstruct frontal albedo images, from multiple non-frontal images. Also a dense 3D shape model of the face is reconstructed, which can be used to generate faces under pose. In the authors’ experiments, the proposed method is able to improve the face recognition scores in more than 90% of the cases. Using the likelihood ratio framework, they show for the same experiment that for data initially unsuitable for forensic use, the reconstructions become meaningful in a forensic context in more than 60% of the cases.
    Original languageEnglish
    Pages (from-to)140-146
    Number of pages7
    JournalIET biometrics
    Issue number2
    Publication statusPublished - 2016


    • SCS-Safety
    • Statistical Analysis
    • Frontal albedo image reconstruction
    • Face recognition score improvement
    • Forensic face comparison process
    • Likelihood ratio framework
    • Dense 3D shape model
    • Dense model-free 3D face reconstruction method
    • Image forensics
    • Image sensors
    • Solid modelling
    • 3D shape refining
    • Image reconstruction
    • Image sequences
    • Face recognition
    • Albedo estimation
    • Lambertian reflectance model
    • Multiple nonfrontal images


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