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A robust pipeline for rapid feature-based pre-alignment of dense range scans

机译:强大的流水线可用于基于特征的密集范围扫描的快速预对准

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摘要

Aiming at reaching an interactive and simplified usage of high-resolution 3D acquisition systems, this paper presents a fast and automated technique for pre-alignment of dense range images. Starting from a multi-scale feature point extraction and description, a processing chain composed by feature matching and correspondence searching, ranking grouping and skimming is performed to select the most reliable correspondences over which the correct alignment is estimated. Pre-alignment is obtained in few seconds per million point images on a off-the-shelf PC architecture. The experimental setup aimed to demonstrate the system behavior with respect to a set of concurrent requirements and the obtained performance are significant in the perspective of a fast, robust and unconstrained 3D object reconstruction.
机译:为了达到高分辨率3D采集系统的交互式简化用法,本文提出了一种快速自动的技术,用于对密集范围图像进行预对准。从多尺度特征点提取和描述开始,执行由特征匹配和对应关系搜索,等级分组和略读组成的处理链,以选择最可靠的对应关系,据此估计正确的对齐方式。在现成的PC架构上,每百万点图像只需几秒钟即可获得预对准。实验设置旨在证明针对一组并发需求的系统行为以及所获得的性能,对于快速,健壮且不受约束的3D对象重建而言,具有重要意义。

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