Towards Illumination-Invariant 3D Reconstruction Using ToF RGB-D Cameras

C. Kerl, Mohamed Souiai, Jürgen Sturm, D. Cremers
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引用次数: 31

Abstract

Creating textured 3D scans of indoor environments has experienced a large boost with the advent of cheap commodity depth sensors. However, the quality of the acquired 3D models is often impaired by color seams in the reconstruction due to varying illumination (e.g., Shadows or highlights) and object surfaces whose brightness and color vary with the viewpoint of the camera. In this paper, we propose a direct and simple method to estimate the pure albedo of the texture, which allows us to remove illumination effects from IR and color images. Our approach first computes the illumination-independent albedo in the IR domain, which we subsequently transfer to the color albedo. As shadows and highlights lead to over- and underexposed image regions with little or no color information, we apply an advanced optimization scheme to infer color information in the color albedo from neigh boring image regions. We demonstrate the applicability of our approach to various real-world scenes.
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利用ToF RGB-D相机实现光照不变三维重建
随着廉价商品深度传感器的出现,创建室内环境的纹理3D扫描经历了巨大的推动。然而,由于不同的照度(例如,阴影或高光)和物体表面的亮度和颜色随着相机的视点而变化,所获得的3D模型的质量通常会受到重建中的颜色接缝的影响。在本文中,我们提出了一种直接和简单的方法来估计纹理的纯反照率,使我们能够从红外和彩色图像中去除照明影响。我们的方法首先计算红外域中与光照无关的反照率,然后将其转换为彩色反照率。由于阴影和高光会导致曝光过度和曝光不足的图像区域很少或没有颜色信息,我们采用了一种先进的优化方案,从相邻的无聊图像区域推断颜色反照率中的颜色信息。我们展示了我们的方法在各种现实场景中的适用性。
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