RGBD-fusion: Real-time high precision depth recovery

Roy Or-El, G. Rosman, Aaron Wetzler, R. Kimmel, A. Bruckstein
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引用次数: 109

Abstract

The popularity of low-cost RGB-D scanners is increasing on a daily basis. Nevertheless, existing scanners often cannot capture subtle details in the environment. We present a novel method to enhance the depth map by fusing the intensity and depth information to create more detailed range profiles. The lighting model we use can handle natural scene illumination. It is integrated in a shape from shading like technique to improve the visual fidelity of the reconstructed object. Unlike previous efforts in this domain, the detailed geometry is calculated directly, without the need to explicitly find and integrate surface normals. In addition, the proposed method operates four orders of magnitude faster than the state of the art. Qualitative and quantitative visual and statistical evidence support the improvement in the depth obtained by the suggested method.
RGBD-fusion:实时高精度深度恢复
低成本RGB-D扫描仪的普及程度与日俱增。然而,现有的扫描仪往往不能捕捉到环境中的细微细节。本文提出了一种新的深度图增强方法,通过融合强度和深度信息来创建更详细的距离轮廓。我们使用的照明模型可以处理自然场景照明。它集成在一个形状从阴影技术,以提高重建对象的视觉保真度。与之前在该领域的工作不同,直接计算详细的几何形状,而不需要显式地查找和积分表面法线。此外,所提出的方法运行速度比现有技术快4个数量级。定性和定量的视觉和统计证据支持通过建议的方法获得的深度改进。
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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