基于HASM的口形特征点定位

基金项目:

国家自然科学基金(60375007)

北京市自然科学基金(40410031).

详细信息

Oral Features Localization Based on HASM

Beijing Municipal Key Laboratory of Multimedia and Intelligent Software Technology, College of Computer Science, Beijing University of Technology, Beijing 100022, China

摘要: 针对口形特征点定位的准确性问题,提出一种基于HASM(hierarchical active shape model)的口形轮廓定位方法,采用不等步长、不等角度建模策略和口形聚类策略,构建局部纹理模型作为特征点搜索依据,并利用马氏距离选取最佳定位点.试验结果表明,HASM模型的口形特征点定位方法使内唇定位和闭口口形定位的准确率达到90%以上.
- 特征点定位 /
- 主动形状模型 /
- 局部纹理模型 /
- 马氏距离
Abstract: The principal idea of this research for visual speech synthesis realism is that oral features localization provides the precise geometrical information for oral images of speech sound. In this research, Hierarchical Active Shape Model (HASM) is used as local texture model. In the structuring local texture model, the local texture model is the main clue. The optimal oral features localizations are decided by Mahalanobis distance. This research utilizes variable step strategy, variable angle strategy and oral images clustering strategy to greatly improve the accuracy and efficiency of inter lip localization and special lip shape. The result shows that the accuracy and efficiency are up to 90 %.
- features localization /
- active shape mode（ASM） /
- local texture model /
- Mahalanobis distance