Three-Phase Face Recognition Algorithm via Locally Frontal Face Synthesis and Two-Phase Face Recognition

Qing Jie Zhao, Hui Qi, Yu Zhang, Hao Wang

科研成果: 期刊稿件文章同行评审

1 引用 (Scopus)

摘要

Two-phase test sample representation algorithm (TPTSR), which is robust to interference such as occlusion and noise, performs well in face recognition without pose variation. However, its recognition rate will decline when the face pose varies dramatically. To solve this problem, a three-phase test sample representation algorithm was proposed. The first was frontal face synthesizing was a frontal face with small horizontal deflection angle was synthesized using view-library and proposed frontal face synthesizing algorithm. Thus, a frontal face was synthesized as the new test sample. The second was training sample selecting phase, M training samples that make the most contribution were selected to represent the new test sample. The third was decision and recognition phase, a face was recognized using the M training samples. Experiments on some publicly available face recognition benchmarks demonstrate that the proposed 3PTSR algorithm outperforms the state-of-the-art methods in challenging conditions, especially for the face with various poses.

源语言英语
页(从-至)637-643
页数7
期刊Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology
37
6
DOI
出版状态已出版 - 1 6月 2017

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Zhao, Q. J., Qi, H., Zhang, Y., & Wang, H. (2017). Three-Phase Face Recognition Algorithm via Locally Frontal Face Synthesis and Two-Phase Face Recognition. Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 37(6), 637-643. https://doi.org/10.15918/j.tbit1001-0645.2017.06.016