A hierarchical dense deformable model for 3D face reconstruction from skull

  • Authors:
  • Yongli Hu;Fuqing Duan;Baocai Yin;Mingquan Zhou;Yanfeng Sun;Zhongke Wu;Guohua Geng

  • Affiliations:
  • Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing, People's Republic of China 100124;College of Information Science and Technology, Beijing Normal University, Beijing, People's Republic of China 100875;Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing, People's Republic of China 100124;College of Information Science and Technology, Beijing Normal University, Beijing, People's Republic of China 100875;Beijing Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science and Technology, Beijing University of Technology, Beijing, People's Republic of China 100124;College of Information Science and Technology, Beijing Normal University, Beijing, People's Republic of China 100875;Department of Computer Science, Northwest University, Xi'an, People's Republic of China 710069

  • Venue:
  • Multimedia Tools and Applications
  • Year:
  • 2013

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Abstract

3D face reconstruction from skull has been investigated deeply by computer scientists in the past two decades because it is important for identification. The dominant methods construct 3D face from the soft tissue thickness measured at a set of landmarks on skull. The quantity and position of the landmarks are very vital for 3D face reconstruction, but there is no uniform standard for the selection of the landmarks. Additionally, the acquirement of the landmarks on skull is difficult without manual assistance. In this paper, an automatic 3D face reconstruction method based on a hierarchical dense deformable model is proposed. To construct the model, the skull and face samples are acquired by CT scanner and represented as dense triangle mesh. Then a non-rigid dense mesh registration algorithm is presented to align all the samples in point-to-point correspondence. Based on the aligned samples, a global deformable model is constructed, and three local models are constructed from the segmented patches of the eye, nose and mouth. For a given skull, the globe and local deformable models are iteratively matched with it, and the reconstructed facial surface is obtained by fusing the globe and local reconstruction results. To validate the presented method, a measurement in the coefficient domain of a face deformable model is defined. The experimental results indicate that the proposed method has good performance for 3D face reconstruction from skull.