融合单演二值编码的人脸表情识别算法

Facial Expression Recognition Algorithm Based on Monogenic Binary Coding

为提高人脸表情识别算法的识别率和鲁棒性,本文提出一种融合单演二值编码的人脸表情识别算法.该算法运用单演信号分析提取多尺度单演振幅、相位和方向三个正交互补的分量,使用单演二值编码对该三种分量的每个尺度进行编码及划分为多个矩形块子区域,并采用分块Fisher线性判别对其降维并提高识别率.实验结果表明:所提算法比传统人脸表情识别算法具有更高的识别率.此外,遮挡对比实验证明了所提算法比传统算法有更好的鲁棒性.

To improve the recognition rate and robustness of facial expression recognition, a novel facial expression recognition algorithm based on fusion of monogenic binary coding is proposed. This algorithm extracts three orthogonal complementary component products of multi-scale monogenic amplitude, phase and direction respectively by means of monogenic signal analysis, encodes the dimension of each component product using monogenic binary coding and divide each into multiple rectangular regions, and then reduce their dimension and improve their recognition rate by means of Blocked Fisher liner discrimination. Experiment results show that the proposed algorithm has a better recognition rate than the traditional algorithm. Also, occlusion experiments show that it is of better robustness.