High Quality Shape from a Single RGB-D Image under Uncalibrated Natural Illumination

Yudeog Han, Joon-Young Lee, In-So Kweon
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引用次数: 97

Abstract

We present a novel framework to estimate detailed shape of diffuse objects with uniform albedo from a single RGB-D image. To estimate accurate lighting in natural illumination environment, we introduce a general lighting model consisting of two components: global and local models. The global lighting model is estimated from the RGB-D input using the low-dimensional characteristic of a diffuse reflectance model. The local lighting model represents spatially varying illumination and it is estimated by using the smoothly-varying characteristic of illumination. With both the global and local lighting model, we can estimate complex lighting variations in uncontrolled natural illumination conditions accurately. For high quality shape capture, a shape-from-shading approach is applied with the estimated lighting model. Since the entire process is done with a single RGB-D input, our method is capable of capturing the high quality shape details of a dynamic object under natural illumination. Experimental results demonstrate the feasibility and effectiveness of our method that dramatically improves shape details of the rough depth input.
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在未校准的自然照明下,从单个RGB-D图像获得高质量形状
我们提出了一种新的框架来估计具有均匀反照率的漫射物体的详细形状从单个RGB-D图像。为了估计自然光照环境下的精确照明,我们引入了一个由全局模型和局部模型两部分组成的通用照明模型。利用漫反射模型的低维特性,从RGB-D输入估计全局照明模型。局部照明模型表示空间变化的照度,并利用照度的平滑变化特性对其进行估计。利用全局和局部光照模型,我们可以准确地估计自然光照不受控制条件下的复杂光照变化。为了获得高质量的形状捕获,我们采用了一种基于阴影的形状捕获方法。由于整个过程是用一个RGB-D输入完成的,我们的方法能够在自然光照下捕获动态物体的高质量形状细节。实验结果证明了该方法的可行性和有效性,显著改善了粗深度输入的形状细节。
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