一个完整的解决方案,从亲属对应的一般化相对位置估计的完整解决方案
概括
本研究介绍了最小的解决方案,用于估计相机相对位置,使用两个亲缘对应 (AC),改善计算机视觉任务在多摄像头系统. 这些新方法在自动驾驶等应用中是高效和有效的.
科学领域:
- 计算机视觉 计算机视觉
- 几何计算机视觉 几何计算机视觉
- 机器人技术 机器人技术 机器人技术
背景情况:
- 亲缘对应 (AC) 越来越多地用于计算机视觉,比点对应 (PC) 有优势.
- 一个单一的AC通常为相对姿势估计提供三个约束.
- 多视角摄像系统对于自动驾驶汽车和增强现实至关重要.
研究的目的:
- 开发用于6DoF相对立场估计的第一个全面的最小解决方案套件,在多摄像头系统中只使用两个AC.
- 为了满足在有限对应的场景中对强大的模型适配的需求.
- 为了提高计算效率和解决方案的紧性在相对立场估计.
主要方法:
- 在两个视图中对两个AC的所有配置进行分析.
- 为所有已识别的最小案例开发最小的解决方案.
- 使用隐藏变量技术来消除翻译参数.
- 使用凯利参数或四次元来表示旋转.
- 引入广义相对论的新约束构成了问题.
主要成果:
- 拟议的方法提供了一套全面的最小解决方案,用于使用两个AC估计6DoF相对立场.
- 对于两个AC的所有最小配置,Solvers是导出的.
- 新的约束导致了更紧的解决方案,解决方案较少.
- 在合成和现实数据上的实验验证证证了高效率和计算效率.
结论:
- 在多摄像头系统中,基于亲缘对应的解决方案提供了强大而高效的解决方案,用于对应姿势的估计.
- 开发的最小解析器对于计算机视觉中的强大的几何计算是有价值的.
- 这项工作推进了对自动驾驶和增强现实等应用的相对位置估计的最新技术.
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