对于视力受损的个人来说,独立寻找路径与避免碰撞
Tadeh Ghahremanians1, Hossein Mahvash Mohammadi2
1University of Isfahan, Isfahan, 8174673441, Iran.
Scientific reports
|October 10, 2025
概括
这项研究引入了一个新的计算机视觉框架,用于视力受损的导航. 这种新的全光细分方法增强了路径查找和避免碰撞的功能,性能优于现有系统.
科学领域:
- 计算机视觉 计算机视觉
- 人工智能的人工智能
- 辅助技术 辅助技术 辅助技术
背景情况:
- 图像细分对于视力受损的导航至关重要,但需要详细的空间信息.
- 现有的方法在为安全航行提供强大和高性能解决方案方面面临挑战.
研究的目的:
- 为有效的路径识别系统提出一种全新的全光细分框架.
- 为了将强大的避免碰撞与视力受损人士的高性能相结合.
- 支持视觉假肢的实时反以支持未来的整合.
主要方法:
- 开发了一种使用ResNet101-FPN编码器-解码器架构的单阶段实例分割方法.
- 创建了一个定制的泛光标记数据集,以满足视力受损人士的需求.
- 通过使用泛光质量 (PQ) 度量,对模型进行了定性和定量评估.
主要成果:
- 拟议的方法获得了全视质量 (PQ) 评分,比最近的全视分段技术高4.092分.
- 与现有的路径系统相比,证明了更高的准确性和效率.
- 在各种天气条件下展示了有效性.
结论:
- 新型全光学细分框架为先进的路径查找系统提供了坚实的基础.
- 定制数据集和ResNet101-FPN架构有助于提高辅助技术的性能.
- 这项工作推进了计算机视觉应用程序,以提高视力障碍者的独立性和安全性.
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