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相关实验视频

Updated: Jul 18, 2025

Video Movement Analysis Using Smartphones ViMAS: A Pilot Study
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Video Movement Analysis Using Smartphones ViMAS: A Pilot Study

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基于使用智能手机的三维重建,自动测量树的高度.

Yulin Shen1, Ruwei Huang1, Bei Hua1

  • 1School of Computer, Electronics and Information, Guangxi University, Nanning 530004, China.

Sensors (Basel, Switzerland)
|August 26, 2023
PubMed
概括
此摘要是机器生成的。

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一个新的智能手机应用程序使用3D重建来准确测量树的高度. 这种自动化方法通过避免复杂的校准来简化森林库存,达到3.20%的平均误差.

科学领域:

  • 林业科学 林业科学
  • 计算机视觉 计算机视觉
  • 遥感 遥感 遥感 遥感

背景情况:

  • 树木的高度对于森林库存,库存量和生长评估至关重要.
  • 基于智能手机的近距离摄影仪表提供了低成本,非破坏性的测量,但具有操作限制.
  • 现有的方法需要特定的摄像头角度,距离和拍摄前校准,这在自然环境中带来了挑战.

研究的目的:

  • 开发一种自动化和高效的树木高度测量方法,使用基于智能手机的3D重建.
  • 为了克服在复杂的森林环境中传统光谱的操作不便.
  • 为了实现适用于森林调查的准确树木高度测量.

主要方法:

  • 使用ARCore和Midas.Net生成绝对深度地图.
  • 一个改进的Attention-UNet模型结合了深度地图来生成精确的树木面具.
  • 彩色图像和深度地图被合并为3D点云生成,随后是树点云提取.
  • 树的高度是通过分析提取的树点云的轴对齐的边界框来确定的.

主要成果:

  • 开发的方法被集成到一个高效和自动化的Android应用程序中.
  • 该方法表现出高精度,平均相对误差为3.20%.
关键词:
深度估计估计的估计.深度学习是一种深度学习.功能融合功能融合功能图像细分 图像细分智能手机的智能手机智能手机的智能手机.三维重建的三维重建树的高度测量 树的高度测量

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  • 在实际射击距离范围为2至17米的范围内获得了准确的测量.

    • 结论:

    • 拟议的3D重建方法为树木高度测量提供了实用和自动化的解决方案.
    • 该方法满足了森林调查的准确性要求,提高了效率并减少了操作复杂性.
    • 基于智能手机的3D重建为传统森林库存技术提供了可行的替代方案.