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  • 1.
    Braude, I.
    et al.
    Department of Computer Science, Drexel University, Philadelphia, PA, United States.
    Marker, J.
    Department of Computer Science, Drexel University, Philadelphia, PA, United States.
    Museth, Ken
    Linköping University, Department of Science and Technology, Digital Media. Linköping University, The Institute of Technology.
    Nissanov, J.
    Department of Neurobiology and Anatomy, Drexel University College of Medicine, Philadelphia, PA, United States.
    Breen, D.
    Department of Computer Science, Drexel University, Philadelphia, PA, United States.
    Contour-based surface reconstruction using MPU implicit models2007In: Graphical Models, ISSN 1524-0703, E-ISSN 1524-0711, Vol. 69, no 2, p. 139-157Article in journal (Refereed)
    Abstract [en]

    This paper presents a technique for creating a smooth, closed surface from a set of 2D contours, which have been extracted from a 3D scan. The technique interprets the pixels that make up the contours as points in R3 and employs multi-level partition of unity (MPU) implicit models to create a surface that approximately fits to the 3D points. Since MPU implicit models additionally require surface normal information at each point, an algorithm that estimates normals from the contour data is also described. Contour data frequently contains noise from the scanning and delineation process. MPU implicit models provide a superior approach to the problem of contour-based surface reconstruction, especially in the presence of noise, because they are based on adaptive implicit functions that locally approximate the points within a controllable error bound. We demonstrate the effectiveness of our technique with a number of example datasets, providing images and error statistics generated from our results. © 2006 Elsevier Inc. All rights reserved.

  • 2. Fratarcangeli, M.
    et al.
    Schaerf, M.
    University of Rome La Sapienza, Department of Computer and Systems Science, Via Salaria 113, 00196 Rome, Italy.
    Forchheimer, Robert
    Linköping University, The Institute of Technology. Linköping University, Department of Electrical Engineering.
    Facial motion cloning with radial basis functions in MPEG-4 FBA2007In: Graphical Models, ISSN 1524-0703, E-ISSN 1524-0711, Vol. 69, no 2, p. 106-118Article in journal (Refereed)
    Abstract [en]

    Facial Motion Cloning (FMC) is the technique employed to transfer the motion of a virtual face (namely the source) to a mesh representing another face (the target), generally having a different geometry and connectivity. In this paper, we describe a novel method based on the combination of the Radial Basis Functions (RBF) volume morphing with the encoding capabilities of the widely used MPEG-4 Facial and Body Animation (FBA) international standard. First, we find the morphing function G(P) that precisely fits the shape of the source into the shape of the target face. Then, all the MPEG-4 encoded movements of the source face are transformed using the same function G(P) and mapped to the corresponding vertices of the target mesh. By doing this, we obtain, in a straightforward and simple way, the whole set of the MPEG-4 encoded facial movements for the target face in a short time. This animatable version of the target face is able to perform generic face animation stored in a MPEG-4 FBA data stream. © 2006 Elsevier Inc. All rights reserved.

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