• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2006, Vol. 28 ›› Issue (6): 62-65.

• 论文 • 上一篇    下一篇

表情特征区域归一化误差分析及矫正

应伟[1] 邹北骥[2] 周凌[1] 孙家广[3]   

  • 出版日期:2006-06-01 发布日期:2010-05-20

  • Online:2006-06-01 Published:2010-05-20

摘要:

几何归一化处理对于表情特征信息的有效提取具有重要意义,常用的归一化方法由于选择的基准特征在表情变化时存在不稳定性,容易造成归一化后的结果存在误差.本文结合光流特征提取方法分析了归一化误差对表情特征提取的严重影响,并提出了加权优化匹配算法进行误差的矫正.算法以传统模板匹配原理为基础,根据各像素点的运动剧烈程度 分配相应的匹配权值.实验证明,误差得到了有效的矫正,提取的表情特征信息更加真实.

关键词: 表情特征提取 归一化 误差矫正 光流

Abstract:

Generally the geometrical normalization process is important to the extraction of facial expression features. In commonly used normalization methods,  the unstability of the fiducial features resulted from facial motions always causes normalization errors. Making use of the optical flow method, the pap er analyzes quantitatively the serious influence on feature extraction caused by normalization errors,and proposes a weighted optimal matching algorithm  to solve it. The algorithm is founded on the basis of the template matching theory, and  rees when carrying on the calculation of correlative coefficients. Experimental results show that the algorithm can restrain the disturbance that normal ization error produces,and facial expression features can be extracted more accurately.

Key words: (human facial feature extraction, normalization, error-correction, optical flow)