A Vision-Based Method for Recognizing Non-manual Information in Japanese Sign Language
A Vision-Based Method for Recognizing Non-manual Information in Japanese Sign Language
复制标题
基于视觉的日本手语非手动信息识别方法
DOI：
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发表时间：
2000
期刊：
影响因子：
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通讯作者：
H. Sagawa
中科院分区：
文献类型：
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作者：
Ming Xu;B. Raytchev;K. Sakaue;O. Hasegawa;A. Koizumi;M. Takeuchi;H. Sagawa
本文提出了一种基于视觉的日语手语非手动信息识别方法。这种新的情态信息提供了对JSL分词和解释有用的语法约束。我们的注意力集中在头部运动上，这是JSL中最主要的非手动信息。我们设计了一种交互式颜色建模方案，用于鲁棒人脸检测。两个摄像机垂直放置，拍摄JSL用户的正面和侧面图像，头部运动分为11种模式。采用基于矩的特征和统计运动特征来表示这些运动模式。采用线性判别分析方法对运动特征进行分类。初步实验结果表明，该方法具有良好的识别率，可以实时实现。
This paper describes a vision-based method for recognizing the nonmanual information in Japanese Sign Language (JSL). This new modality information provides grammatical constraints useful for JSL word segmentation and interpretation. Our attention is focused on head motion, the most dominant non-manual information in JSL. We designed an interactive color-modeling scheme for robust face detection. Two video cameras are vertically arranged to take the frontal and profile image of the JSL user, and head motions are classified into eleven patterns. Moment-based feature and statistical motion feature are adopted to represent these motion patterns. Classification of the motion features is performed with linear discrimant analysis method. Initial experimental results show that the method has good recognition rate and can be realized in real-time.