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ACCURATE 3D RECONSTRUCTION VIA SURFACE-CONSISTENCY

机译:通过表面一致性准确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:我们提出了一种算法,其融合多视图立体声(MVS)和光度立体声,以重建由多个摄像机拍摄的多个摄像机拍摄的物体的3D模型。首先,我们通过光度立体技术获得由Albedo缩放的表面正常。然后,提出基于缩放正常的新对应匹配方法,即表面一致性度量,通过三角扫描获取像素的精确3D位置。在过滤点云后,施加泊松表面重建以获得水密网格。该算法已经基于我们的多摄像机和多光获取系统实现。我们通过完全重建挑战真实对象的重建来验证方法,并通过实验显示这种技术可以大大提高先前的MVS结果。

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