Reconstructing a Whole Face Image from a Partially Damaged or Occluded Image by Multiple Matching

  • Bon-Woo Hwang
  • Seong-Whan Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)

Abstract

The problem we address in this paper is, given a facial image that is partially occluded or damaged by noise, to reconstruct a whole face. A key process for the reconstruction is to obtain the correspondences between the input image and the reference face. We present a method that matches an input image with multiple example images that are generated from a morphable face model. From the matched feature points, shape and texture of the full face are inferred by the non-iterative data completion algorithm. Compared with single matching with the particular “reference face”, this multiple matching method increases the robustness of the matching. The experimental results of applying the algorithm to face images that are contaminated by Gaussian noise and those which are partially occluded show that the reconstructed faces are plausible and similar to the original ones.

Keywords

Face reconstruction morphable face model SIFT feature data completion 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Bon-Woo Hwang
    • 1
  • Seong-Whan Lee
    • 2
  1. 1.The Robotics Institute, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213USA
  2. 2.Center for Artificial Vision Research, Korea University, Anam-dong, Seongbuk-gu, Seoul 136-713Korea

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