Dense 3D Reconstruction method using Coplanarities and Metric Constraints for Line Laser Scanning

Hiroshi Kawasaki, Furukawa Ryo
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引用次数: 13

Abstract

In this paper, we propose a novel method to achieve both dense 3D reconstruction of the scene and estimation of the camera intrinsic parameters by using coplanarities and other constraints (e.g. orthogonalities or parallelisms) derived from relations between planes in the scene and reflected curves of line lasers captured by a single camera. In our study, we categorize coplanarities in the scene into two types: implicit coplanarities, which can be observed as reflected curves of line lasers, and explicit coplanarities, which are, for example, observed as walls of a building. By using both types of coplanarities, we can construct simultaneous equations and can solve them up to four degrees of freedom. To upgrade the solution to the Euclidean space and estimate the camera intrinsic parameters, we can use metric constraints such as orthogonalities of the planes. Such metric constraints are given by, for example, observing the corners of rectangular boxes in the scene, or using special laser projecting device composed of two line lasers whose laser planes are configured to be perpendicular.
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基于共面性和度量约束的线激光扫描密集三维重建方法
在本文中,我们提出了一种新的方法来实现场景的密集三维重建和相机固有参数的估计,该方法使用共平面性和其他约束(例如正交性或平行性),这些约束来自场景中的平面与单个相机捕获的线激光反射曲线之间的关系。在我们的研究中,我们将场景中的共面性分为两种类型:隐式共面性,可以通过线激光的反射曲线观察到,以及显式共面性,例如,可以通过建筑物的墙壁观察到。通过使用这两种类型的共面性,我们可以构建联立方程,并可以在四个自由度内求解它们。为了将解升级到欧几里德空间并估计相机的内在参数,我们可以使用度量约束,如平面的正交性。例如,通过观察场景中矩形框的角,或使用由两个激光平面垂直配置的线激光器组成的特殊激光投影装置来给出这种度量约束。
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3D Challenges and a Non-In-Depth Overview of Recent Progress A Comparative Analysis of Depth-Discontinuity and Mixed-Pixel Detection Algorithms Image-based Model Completion Dense 3D Reconstruction method using Coplanarities and Metric Constraints for Line Laser Scanning Data-Driven Feature-Based 3D Face Synthesis
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