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Expression-robust 3D face recognition based on feature-level fusion and feature-region fusion

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Abstract

3D face shape is essentially a non-rigid free-form surface, which will produce non-rigid deformation under expression variations. In terms of that problem, a promising solution named Coherent Point Drift (CPD) non-rigid registration for the non-rigid region is applied to eliminate the influence from the facial expression while guarantees 3D surface topology. In order to take full advantage of the extracted discriminative feature of the whole face under facial expression variations, the novel expression-robust 3D face recognition method using feature-level fusion and feature-region fusion is proposed. Furthermore, the Principal Component Analysis and Linear Discriminant Analysis in combination with Rotated Sparse Regression (PL-RSR) dimensionality reduction method is presented to promote the computational efficiency and provide a solution to the curse of dimensionality problem, which benefit the performance optimization. The experimental evaluation indicates that the proposed strategy has achieved the rank-1 recognition rate of 97.91 % and 96.71 % based on Face Recognition Grand Challenge (FRGC) v2.0 and Bosphorus respectively, which means the proposed approach outperforms state-of-the-art approach.

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Acknowledgments

The authors would like to thank the editorial office and five anonymous reviewers who gave valuable comments and helpful suggestions which greatly improved the quality of the paper.

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Authors and Affiliations

  1. Department of Automation, Southeast University, Nanjing, 210096, Jiangsu, China

    Xing Deng, Feipeng Da & Haijian Shao

  2. Key Laboratory of Measurement and Control for Complex System of Ministry of Education, Southeast University, Nanjing, 210096, Jiangsu, China

    Xing Deng, Feipeng Da & Haijian Shao

Authors
  1. Xing Deng
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  2. Feipeng Da
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  3. Haijian Shao
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Corresponding author

Correspondence to Feipeng Da.

Additional information

This research is supported by National Natural Science Foundation of China (No. 51175081, No. 51475092, No. 61405034), Doctoral Fund of Ministry of Education of China (No. 20130092110027).

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Deng, X., Da, F. & Shao, H. Expression-robust 3D face recognition based on feature-level fusion and feature-region fusion. Multimed Tools Appl 76, 13–31 (2017). https://doi.org/10.1007/s11042-015-3012-8

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  • DOI: https://doi.org/10.1007/s11042-015-3012-8

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