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摘要: 提出了一种基于排除算法的快速三维人脸识别方法. 首先, 利用主成分分析(Principal component analysis, PCA)对自动切割的不同姿态人脸进行校正, 将所有人脸转换到统一的坐标系下; 然后提取人脸侧面轮廓线, 利用基于LTS-Hausdorff距离的轮廓线对齐方法对库集对象进行排除; 最后, 采用基于刚性区域的改进迭代最近点(Iterative closest point, ICP)算法对剩余的库集模型进行精确匹配, 给出最终识别结果. 在FRGC V2.0人脸数据库的实验结果表明, 该方法具有较好的实时性和鲁棒性.
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关键词:
- 三维人脸识别 /
- 侧面轮廓线匹配 /
- 排除算法 /
- Hausdorff距离 /
- 迭代最近点
Abstract: A rapid method for 3D face recognition based on rejection algorithm is proposed. First, the automatically segmented face with a different pose is normalized by means of principal component analysis (PCA), and transformed into the uniform pose coordinate system. Then, the central profile is extracted and matched based on the least trimmed square Hausdorff distance (LTS-HD) to form a rejection classifier which can eliminate a large number of candidate faces. Finally, the remaining faces are verified using a novel region-based iterative closest point (ICP) algorithm, and the result of the recognition is obtained. The simulation experiment on FRGC V2.0 database demonstrates that the proposed method is simple, efficient, and robust. -
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