葡萄MOTS:无人机葡萄园数据集与MOTS葡萄束注释从多个角度记录,以增强对象检测和跟踪
Mar Ariza-Sentís1, Kaiwen Wang1, Zhen Cao1
1Information Technology Group, Wageningen University & Research, 6708 PB Wageningen, Netherlands.
Data in brief
|May 3, 2024
概括
这项研究通过使用无人机的多个视角来解决水果检测和跟踪方面的不足. 它强调需要更好的数据集,特别是用于葡萄束检测和跟踪,以改善农业技术.
科学领域:
- 农业技术 农业技术
- 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
背景情况:
- 对象检测和跟踪 (ODT) 算法自动计算水果,减少人类劳动力.
- 手动计数水果是耗时且容易出现错误的,特别是在产量大的情况下.
- 由于水果封闭 (例如,被叶子隐藏),ODT算法难以计数.
研究的目的:
- 解决葡萄束检测和跟踪公共数据集的稀缺问题.
- 通过克服封闭挑战来提高ODT算法的准确性.
- 为了利用无人机 (UAV) 图像进行全面的数据采集.
主要方法:
- 使用对象检测和跟踪算法.
- 使用无人机从多个视角获取图像和视频数据.
- 专注于用于葡萄束检测和跟踪的数据集.
主要成果:
- 识别了不足作为农业ODT的一个关键挑战.
- 强调了采集多角度数据的必要性,以减轻阻塞.
- 他指出,对于葡萄束等特定水果缺乏标记数据集.
结论:
- 多角度无人机数据对于提高水果检测和跟踪精度至关重要.
- 开发全面的标记数据集对于推进农业ODT至关重要.
- 这项研究旨在增强农民的自动化水果计数系统.
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