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Depth Edge Filtering Using Parameterized Structured Light Imaging

机译:使用参数化结构化光成像进行深度边缘滤波

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This research features parameterized depth edge detection using structured light imaging that exploits a single color stripes pattern and an associated binary stripes pattern. By parameterized depth edge detection, we refer to the detection of all depth edges in a given range of distances with depth difference greater or equal to a specific value. While previous research has not properly dealt with shadow regions, which result in double edges, we effectively remove shadow regions using statistical learning through effective identification of color stripes in the structured light images. We also provide a much simpler control of involved parameters. We have compared the depth edge filtering performance of our method with that of the state-of-the-art method and depth edge detection from the Kinect depth map. Experimental results clearly show that our method finds the desired depth edges most correctly while the other methods cannot.
机译:这项研究的特点是使用结构化光成像技术对深度边缘进行参数化检测,该技术利用单色条纹图案和关联的二进制条纹图案。通过参数化深度边缘检测,我们指的是在给定距离范围内深度差大于或等于特定值的所有深度边缘的检测。尽管先前的研究尚未正确处理阴影区域,这会导致出现双边缘,但我们通过有效识别结构化光图像中的色带,使用统计学习来有效去除阴影区域。我们还提供了对所涉及参数的简单得多的控制。我们将我们的方法的深度边缘过滤性能与最新技术的性能和Kinect深度图中的深度边缘检测进行了比较。实验结果清楚地表明,我们的方法最正确地找到了所需的深度边缘,而其他方法则无法。

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