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MATHEMATICAL MORPHOLOGY BASED AUTOMATED CONTROL POINT DETECTION FROM HUMAN FACIAL IMAGE

机译:基于数学形态学的人脸图像自动控制点检测

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摘要

The ultimate goal of this research is to incorporate facial animation based on image morphing in a very narrow bandwidth video transmission, especially in video conferencing, news telecast etc., where the background as well as the object in the image change little. As a part of the whole work, in this paper, an efficient mathematical morphology-based facial feature control point detection technique is proposed. By facial feature control point we mean facial feature (i.e. eye, lip etc.) surrounding points and other important points in the face which can be utilized to create facial animation based on image metamorphosis. In the experiment, mathematical morphology tools are used both for filtering and pattern matching. At first, intensity-independent, color-based segmentation is used with some morphological processing on the input image to separate skin regions. Then, the parallel eye segments are searched by erosion of the edge-thinned image with eye corner structuring elements. By combining them, the probable eye segment pair is identified. Then, using facial structural knowledge, the lips and other control points are detected. The accuracy of the proposed method is within quite acceptable limits; moreover, the method is capable of working with images of average quality or close to average quality.
机译:这项研究的最终目标是将基于图像变形的面部动画并入非常窄带宽的视频传输中,特别是在视频会议,新闻电视广播等场合,其中背景以及图像中的对象变化很小。作为整个工作的一部分,本文提出了一种有效的基于数学形态学的面部特征控制点检测技术。面部特征控制点是指围绕面部中的点和其他重要点的面部特征(即眼睛,嘴唇等),可用于基于图像变形来创建面部动画。在实验中,数学形态学工具用于过滤和模式匹配。首先,将强度独立的基于颜色的分割与输入图像上的某些形态处理一起使用,以分离皮肤区域。然后,通过用眼角结构元素腐蚀边缘变淡的图像来搜索平行的眼段。通过组合它们,可以识别可能的眼线段对。然后,使用面部结构知识,检测嘴唇和其他控制点。所提出方法的准确性在完全可以接受的范围内。此外,该方法能够处理平均质量或接近平均质量的图像。

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