Jaehyun So1, Sanghun Han1, Youngtak Kim1, Hwanik Chung2, Youngjoon Han1
(1. Department of Electronic Engineering, Soongsil University, Seoul 156-743, Korea;2. Department of Computer Science, Kyungbok University, Pocheon 487-717, Korea)
Abstract： This paper proposes the efficient model building in active appearance model (AAM) for the rotated face. Finding an exact region of the face is generally difficult due to different shapes and viewpoints. Unlike many papers about the fitting method of AAM, this paper treats how images are chosen for fitting of the rotated face in modelling process. To solve this problem, databases of facial rotation and expression are selected and models are built using Procrustes method and principal component analysis (PCA). These models are applied in fitting methods like basic AAM fitting, inverse compositional alignment (ICA), project-out ICA, normalization ICA, robust normalization inverse compositional algorithm (RNIC) and efficient robust normalization algorithm (ERN). RNIC and ERN can fit the rotated face in images efficiently. The efficiency of model building is checked using sequence images made by ourselves.
Key words： active appearance model (AAM); Procrustes alignment; principal component analysis (PCA); inverse compositional alignment (ICA); project-out ICA; ormalization ICA; robust normalization inverse compositional algorithm (RNIC); efficient robust normalization algorithm (ERN)
CLD number： TP391.41 Document code： A
Article ID： 1674-8042(2013)04-0346-03 doi： 10.3969/j.issn.1674-8042.2013.04.010
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