在动态环境中解决异质光检测和距离相机对齐挑战:对物体检测的回顾
Yujing Wang1,2, Abdul Hadi Abd Rahman3, Fadilla 'Atyka Nor Rashid3
1Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.
Sensors (Basel, Switzerland)
|December 17, 2024
概括
本文调查了使用LiDAR和摄像头数据进行3D物体检测的20多种异质对齐方法,重点关注动态环境. 它强调了多式联通传感器融合的挑战和未来研究方向.
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
- 自主系统 自主系统
背景情况:
- 对象检测对于自主系统至关重要,它利用来自LiDAR和摄像头传感器的异质数据.
- 现有的审查往往忽视了调整多式联运数据的复杂性,特别是在动态环境中.
研究的目的:
- 在动态环境中调查和分析用于3D对象检测的异质LiDAR相机对齐方法.
- 提供对齐技术的分类,并确定研究缺口.
主要方法:
- 对20多种对齐方法 (2019-2024) 的综合文献综述.
- 专注于动态环境中的异质数据对齐挑战.
- 对各种方法的优点和局限性的比较分析.
主要成果:
- 对于3D对象检测的异质数据对齐方法的分类.
- 确定关键挑战,包括动态环境,传感器融合,可扩展性和实时处理.
结论:
- 在动态场景中,异质对齐对于准确的3D对象检测至关重要.
- 未来的研究应该解决已识别的限制,以推进多式联络传感器融合.
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