世界的袋子,用于即时大规模定位
IEEE transactions on visualization and computer graphics
|October 2, 2023
概括
这项研究引入了一种新的几何场景描述,用于在移动设备上高效的大规模定位. 该方法通过使用轻量级功能来估计姿势,实现准确,跨平台的增强现实体验.
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
- 人与计算机的交互
背景情况:
- 准确的本地化对于移动增强现实 (AR) 应用程序至关重要.
- 现有的方法通常依赖于基于外观的特性,限制了不同平台上的性能,并需要大量的计算资源.
- 在多个设备上进行可扩展和高效的本地化仍然是一个挑战.
研究的目的:
- 开发一种新的场景描述方法,仅使用几何约束来进行大规模本地化.
- 为了使移动AR设备在各种平台上实现高效的本地化和构成估计.
- 通过跨平台本地化促进AR体验的共享.
主要方法:
- 一种新的场景描述方法,利用紧的几何特征和一个字袋模型来描述不同的场景.
- 扩展紧的世界与一个高效的搜索数据结构快速定位.
- 在多个移动平台上实施和测试,包括HoloLens 2和iPad.
主要成果:
- 通过全面的实验,证明了新型几何定位方法的准确性,性能和可扩展性.
- 拟议的方法轻便快速,适合在资源有限的移动设备上部署.
- 有效的跨平台本地化能力的验证.
结论:
- 开发的几何场景描述使移动AR的高效和准确的大规模定位成为可能.
- 该方法的轻量级和快速性质支持在各种移动平台上部署.
- 高效的跨平台本地化是共享增强现实体验的关键推动因素.
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