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Accurate 3D reconstruction via surface-consistency

机译:通过表面一致性进行精确的3D重建

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摘要

We present an algorithm that fuses Multi-view stereo (MVS) and photometric stereo to reconstruct 3D model of objects filmed by multiple cameras under varying illuminations. Firstly, we obtain the surface normal scaled by albedo for each view through photometric stereo techniques. Then, based on the scaled normal, a new correspondence matching method, namely surface-consistency metric, is proposed to acquire accurate 3D positions of pixels through triangulation. After filtering the point cloud, a Poisson surface reconstruction is applied to obtain a watertight mesh. The algorithm has been implemented based on our multi-camera and multi-light acquisition system. We validate the method by complete reconstruction of challenging real objects and show experimentally that this technique can greatly improve on previous MVS results.
机译:我们提出了一种融合多视图立体声(MVS)和光度学立体声的算法,以重建由多个摄像机在变化的照明条件下拍摄的物体的3D模型。首先,我们通过光度立体技术为每个视图获取按反照率缩放的表面法线。然后,基于缩放后的法线,提出了一种新的对应匹配方法,即表面一致性度量,以通过三角测量来获取像素的准确3D位置。过滤点云后,应用泊松曲面重建以获得水密网格。该算法是基于我们的多相机和多光采集系统实现的。我们通过对具有挑战性的真实对象进行完全重建来验证该方法,并通过实验证明该技术可以大大改善以前的MVS结果。

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