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William A. P. Smith
Researcher at University of York
Publications - 202
Citations - 5631
William A. P. Smith is an academic researcher from University of York. The author has contributed to research in topics: Statistical model & Facial recognition system. The author has an hindex of 35, co-authored 198 publications receiving 4489 citations. Previous affiliations of William A. P. Smith include Imperial College London & Daresbury Laboratory.
Papers
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Book ChapterDOI
Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences
TL;DR: This work proposes a fully automatic method for fitting a 3D morphable model to single face images in arbitrary pose and lighting and demonstrates that this is superior to previous work that uses soft correspondences to form an edge-derived cost surface that is minimised by nonlinear optimisation.
Journal ArticleDOI
Towards a Complete 3D Morphable Model of the Human Head
Stylianos Ploumpis,Evangelos Ververas,Eimear O' Sullivan,Stylianos Moschoglou,Haoyang Wang,Nick Pears,William A. P. Smith,Baris Gecer,Stefanos Zafeiriou +8 more
TL;DR: The most complete 3DMM of the human head to date is presented that includes face, cranium, ears, eyes, teeth and tongue and is used to reconstruct full head representations from single, unconstrained images allowing us to parameterize craniofacial shape and texture.
Journal ArticleDOI
Statistical Modeling of Craniofacial Shape and Texture
TL;DR: This work presents a fully-automatic statistical 3D shape modeling approach and applies it to a large dataset of 3D images, the Headspace dataset, thus generating the first public shape-and-texture 3D morphable model (3DMM) of the full human head.
Book ChapterDOI
Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences
TL;DR: In this paper, the authors propose a non-convex objective function for fitting a 3D morphable model to single face images using only sparse geometric features (edges and landmark points), which can be viewed as forming soft correspondences between model and image edges.
Journal ArticleDOI
Molecular dynamics using atomic-resolution structure reveal structural fluctuations that may lead to polymerization of human Cu–Zn superoxide dismutase
TL;DR: This work has undertaken molecular dynamics calculations to 4,000 ps to reveal an essential step in the formation of the experimentally observed self-aggregations of metal-depleted FALS mutant SOD1, and has implications for the role of demetallated wild-type S OD1 in sporadic cases of ALS.