Abstract
In this paper, we propose a novel and efficient algorithm to reconstruct the 3-D structure of a human face from one or a number of its 2-D images with different poses. In our proposed algorithm, the rotation and translation process from a frontal-view face image to a nonfrontal-view face image is at first formulated as a constrained independent component analysis (cICA) model. Then, the overcomplete ICA problem is converted into a normal ICA problem by incorporating a prior from the CANDIDE 3-D face model. Furthermore, the CANDIDE model is employed to construct a reference signal that is used in both the initialization and the objective function of the cICA model. Moreover, a model-integration method is proposed to improve the depth-estimation accuracy when multiple nonfrontal-view face images are available. An important advantage of the proposed algorithm is that no frontal-view face image is required for the estimation of the corresponding 3-D face structure. Experimental results on a real 3-D face image database demonstrate the feasibility and efficiency of the proposed method.
Original language | English |
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Article number | 5719166 |
Pages (from-to) | 360-370 |
Number of pages | 11 |
Journal | IEEE Transactions on Information Forensics and Security |
Volume | 6 |
Issue number | 2 |
DOIs | |
Publication status | Published - 1 Jun 2011 |
Keywords
- 3-D face reconstruction
- CANDIDE model
- constrained independent component analysis (cICA)
- overcomplete independent component analysis (ICA)
ASJC Scopus subject areas
- Safety, Risk, Reliability and Quality
- Computer Networks and Communications