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A Constrained Hybrid Optimization Algorithm for Morphable Appearance Models

  • Cuiping Zhang
  • Fernand S. Cohen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3757)

Abstract

In this paper, we propose a constrained hybrid optimization algorithm that incorporates several shape constraints into a gradient descent procedure using a novel unbiased cost function. Shape constraints are heuristically derived from face images where the face shape can be directly estimated based on ”motion” analysis. To better locate face contour points regardless of the background, local projection models are used. Experiments show that our algorithm benefits significantly from these shape constraints and achieves a much higher convergent rate compared to the inverse compositional optimization algorithm. We test our algorithm on different face databases, and demonstrate its robustness in presence of various illuminations, background patterns, as well as variations in face expressions.

Keywords

Face Image Motion Estimation Face Database Face Shape Landmark Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Cuiping Zhang
    • 1
  • Fernand S. Cohen
    • 1
  1. 1.Electrical and Computer Engineering departmentDrexel UniversityPhiladelphiaUSA

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