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Feature points matching for face reconstruction based on the window unique property of pseudo-random coded image

机译:基于伪随机编码图像窗口唯一性的人脸重建特征点匹配

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摘要

Structured light vision systems have been successfully used for accurate measurement of the 3D surfaces of an object, in which a pseudo-random coded structured light image pattern is projected onto the target object through a projector, and the coded information image produced by its surface is captured by a CCD camera in order to recover its 3D surfaces. In this kind of computer vision technology, 3D face reconstruction is a hot research topic. This paper presents a method for feature points matching used in 3D reconstruction. In this method, the feature points can be identified exclusively taking advantage of the window unique property of a pseudo-random array. Thus, the matching problem can be solved by finding the correspondence between 2D coordinates of feature points in the pixel image and those in the code of the projected template. Then, the 3D reconstruction can be carried out with only a single image with the benefit of easy operation and simple calculation. An experiment for 3D face reconstruction with simulated data is given. The performances show that this method has high matching precision for object matching of feature points.
机译:结构化光视觉系统已成功用于精确测量对象的3D表面,其中通过投影仪将伪随机编码的结构化光图像图案投影到目标对象上,并且由其表面生成的编码信息图像为由CCD相机捕获以恢复其3D表面。在这种计算机视觉技术中,3D人脸重建是一个热门的研究主题。本文提出了一种用于3D重建的特征点匹配方法。在这种方法中,可以仅利用伪随机数组的窗口唯一属性来识别特征点。因此,可以通过找到像素图像中的特征点的二维坐标与投影模板的代码中的特征点的二维坐标之间的对应关系来解决匹配问题。然后,可以仅使用单个图像进行3D重建,具有易于操作和计算简单的优点。给出了使用模拟数据重建3D人脸的实验。实验表明,该方法对特征点的对象匹配具有较高的匹配精度。

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