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Improved marching tetrahedra algorithm based on hierarchical signed distance field and multi-scale depth map fusion for 3D reconstruction

机译:基于分层有符号距离场和多尺度深度图融合的改进行进四面体算法用于3D重建

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3D reconstruction systems are promoted by developments of both computer hardware and computing technologies. They still remain problems like high expense, low efficiency and inaccuracy. Especially for large-scale scenes, lack of full use of multi-scale depth information will cause blurring and irreal reconstruction results. To solve this problem, we construct the structure of hierarchical signed distance field (H-SDF) and design an improved marching tetrahedra algorithm for multi-scale depth map fusion. In addition, to improve efficiency, we also propose a two-phase search strategy in image feature matching: the bag-of-features model (BOF) is adopted in a coarse search to narrow search scope and then the SIFT descriptor is used in exact matching to pick reconstruction image points. Experiment results indicate that coarse search makes matching time shorter; using the H-SDF to fuse multi-scale depth maps, and isosurface extraction with improved marching tetrahedra algorithm can improve visual effect. (C) 2017 Elsevier Inc. All rights reserved.
机译:计算机硬件和计算技术的发展促进了3D重建系统。它们仍然存在诸如高费用,低效率和不准确的问题。特别是对于大型场景,缺乏充分利用多尺度深度信息将导致模糊和不真实的重建结果。为了解决这个问题,我们构造了分层有符号距离场(H-SDF)的结构,并设计了一种用于多尺度深度图融合的改进行进四面体算法。此外,为了提高效率,我们还提出了一种图像特征匹配的两阶段搜索策略:在粗糙搜索中采用特征包模型(BOF)缩小搜索范围,然后精确使用SIFT描述符匹配以选择重建图像点。实验结果表明,粗搜索可以缩短匹配时间。使用H-SDF融合多尺度深度图,并使用改进的行进四面体算法进行等值面提取可以改善视觉效果。 (C)2017 Elsevier Inc.保留所有权利。

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