单眼绝对深度估计从运动为小型无人驾驶飞行器通过基于几何尺度的恢复尺度的运动
Chuanqi Zhang1, Xiangrui Weng1, Yunfeng Cao1
1College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China.
Sensors (Basel, Switzerland)
|July 27, 2024
概括
本研究引入了一种使用单眼视觉用于无人机 (UAV) 绝对深度估计的新方法. 它克服了规模问题,为空中导航提供了准确的3D感知.
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
- 航空航天工程 航空航天工程
背景情况:
- 无监督的单眼深度估计对于智能车辆至关重要,但往往无法提供绝对深度.
- 现有的方法主要集中在地面车辆上,忽视无人机 (UAV).
- 规模模两可的问题限制了单眼深度估计的实际应用.
研究的目的:
- 为无人机开发一种新的无人监督单眼深度估计方法.
- 为了解决尺度问题,并使物理单位的绝对深度预测成为可能.
- 为了将深度估计能力扩展到非结构化的空中场景.
主要方法:
- 基于几何学的尺度恢复算法被用作后处理步骤.
- 使用了连续图像和导航传感器姿势数据之间的特征对应.
- 一个多视图几何模型计算绝对深度生成的比例系.
主要成果:
- 提出的方法成功地从单眼视觉生成无人机的绝对深度地图.
- 在中空数据集和定制数据上的实验验证实了该方法的有效性和稳定性.
- 该方法将无监督深度估计从非结构化环境中的相对值扩展到绝对值.
结论:
- 这种新的方法使无人机只使用单眼相机和导航传感器能够准确地估计无人机的绝对深度.
- 这一进步对于实现空中机器人和自主导航的下游任务具有重要意义.
- 这项研究弥合了将单眼深度估计应用于无人机的关键差距.
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