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Fusion of Depth Maps with Multiple Scales

机译:深度图与多比例尺的融合

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Multi-view stereo systems can produce depth maps with large variations in viewing parameters, yielding vastly different sampling rates of the observed surface. We present a new method for surface reconstruction by integrating a set of registered depth maps with dramatically varying sampling rate. The method is based on the construction of a hierarchical signed distance field represented in an incomplete primal octree by incrementally adding triangulated depth maps. Due to the adaptive data structure, our algorithm is able to handle depth maps with varying scale and to consistently represent coarse, low-resolution regions as well as small details contained in high-resolution depth maps. A final surface mesh is extracted from the distance field by construction of a tetrahedral complex from the scattered signed distance values and applying the Marching Tetrahedra algorithm on the partition. The output is an adaptive triangle mesh that seamlessly connects coarse and highly detailed regions while avoiding filling areas without suitable input data.
机译:多视图立体系统可以生成深度图,这些深度图的视图参数存在很大差异,从而产生了被观察表面的截然不同的采样率。我们提出了一种新的表面重建方法,其方法是将一组已注册的深度图与采样率急剧变化进行集成。该方法基于通过增量添加三角深度图来构建在不完整原始八叉树中表示的分层有符号距离场的方法。由于自适应数据结构,我们的算法能够处理变化比例的深度图,并始终如一地表示高分辨率的深度图中包含的粗略,低分辨率区域以及小细节。通过从散布的有符号距离值构造四面体复合体,并在分区上应用Marching Tetrahedra算法,从距离场中提取最终的表面网格。输出是自适应三角形网格,可无缝连接粗略区域和高度详细区域,同时避免在没有合适输入数据的情况下填充区域。

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