The Research of Depth Perception Method Based on Sparse Random Grid

Dongxue Li, Fang Xu, Fengshan Zou, P. Di, Hongyu Wang
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Abstract

In this paper, we propose a high-resolution depth sensing method based on structured light. In 3D contour scanning, passive binocular stereo vision is difficult to obtain enough 3D information for objects with inconspicuous surface features. To solve this problem, based on the binocular stereo vision principle and the structured light projection method in active vision, a method of obtaining sparse depth based on random mesh is proposed. Four templates are projected onto the surface of the object, which are random meshes and three templates with phase difference. In addition, the relative phase image is calculated according to the three-step phase-shifting mode. Finally, the depth map calculated in the conventional structured light method. In this paper, we demonstrate the effectiveness algorithm to show that our depth sensing are more accurate and resolution than the existing methods in the experiments.
基于稀疏随机网格的深度感知方法研究
本文提出了一种基于结构光的高分辨率深度传感方法。在三维轮廓扫描中,被动双目立体视觉对于表面特征不明显的物体难以获得足够的三维信息。为解决这一问题,基于双目立体视觉原理和主动视觉中的结构光投影方法,提出了一种基于随机网格的稀疏深度获取方法。在物体表面投影4个模板,分别是随机网格和3个相位差模板。此外,根据三步移相模式计算了相对相位图像。最后,用常规结构光法计算深度图。在本文中,我们通过实验验证了算法的有效性,表明我们的深度感知方法比现有的方法具有更高的精度和分辨率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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