计算机与数字工程Issue(3)：396-399,427,5.DOI:10.3969/j.issn1672-9722.2015.03.012
一种基于特征融合降维的表情识别算法*
Expression Recognition Based on Feature Fusion Method for Dimensionality Reduction
张续 1吴松明 1张辉 1童小念1
作者信息
- 1. 中南民族大学计算机科学学院 武汉 430074
- 折叠
摘要
Abstract
In order to reduce the dimensionality and the calculation of expression recognition ,a new method based on the traditional framework is used .Firstly ,features of expression images were extracted with Gabor wavelet of the prepro‐cessed images .Then ,getting the number of the image which has the largest pixel value as the new feature for the eight dif‐ferent orientations on the same scale .So the dimension of characteristic will be reduced to 1/8 of the original .Finally ,count‐ing the feature of fused image which has divided into blocks by statistical histogram .And treating the statistical information as the final feature for classification .Experimental results show that the method reduces the computational of classification of the images in the context of guaranteeing facial expression recognition rate and also improves the system efficiency .关键词
Gabor滤波器/表情识别/特征融合/直方图统计/分类/降维Key words
Gabor filter/facial expression recognition/feature fusion/histogram/classification/dimensionality reduction分类
信息技术与安全科学引用本文复制引用
张续,吴松明,张辉,童小念..一种基于特征融合降维的表情识别算法*[J].计算机与数字工程,2015,(3):396-399,427,5.
