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单眼视觉SLAM,视觉测距,以及应用到3D重建的运动方法的结构:一个全面的调查

Erick P Herrera-Granda^1,2,3, Juan C Torres-Cantero², Diego H Peluffo-Ordóñez^3,4

¹Department of Mathematics, Escuela Politécnica Nacional, Ladrón de Guevara E11-235, Quito, 170525, Ecuador.

|September 23, 2024

概括

单眼同时定位和映射 (SLAM),视觉口径测量 (VO) 和运动结构 (SFM) 提供了可负担的3D重建使用相机. 经典-稀疏-间接和经典-密集-间接方法已经主导了近二十年的单眼3D重建.

科学领域:

计算机视觉计算机视觉
机器人技术机器人技术机器人技术
3D重建的3D重建

背景情况:

单眼同时定位和映射 (SLAM),视觉口径测量 (VO) 和运动结构 (SFM) 是使用单眼相机进行3D重建的关键技术.
这些仅视觉的方法因其成本效益,便携性和在手持设备上广泛的可用性而受到青.

研究的目的:

为3D重建提供单眼SLAM,VO和SFM技术的全面概述和分类.
系统化现有方法,包括经典和机器学习方法,通过详细说明它们的算法和配方.

主要方法:

开发了一个扩展的分类,包括经典,机器学习,直接,间接,密集和稀疏的方法.
对42种方法 (18种经典,24种机器学习) 进行了详细的审查,分析了它们的算法和配方.
基于特定的标准总结了算法,以帮助系统选择和设计.

主要成果:

该研究将42种单眼3D重建方法归类为扩展分类.
系统地介绍了18种经典和24种机器学习方法的关键信息.
对时间趋势的分析揭示了古典分散间接和古典密集间接方法的持续普及.

结论:

这项研究提供了对单眼3D重建技术的结构化理解.
这些发现为研究人员和开发人员在选择或设计3D重建系统时提供了宝贵的见解.
经典分散间接和经典密集间接方法仍然是该领域最普遍的解决方案.

关键词:

单眼RGB三维重建的三维重建一个单眼的SLAM.单眼结构来自运动的运动.单眼视觉测距仪使用单眼视觉测距仪.纯粹的视觉3D重建.

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