通过将模板匹配与几何约束优化相结合,用于行人定位的三眼系统
Jinjing Zhao1, Sen Huang1, Yancheng Li1
1School of Electronics, Peking University, Beijing 100871, China.
Sensors (Basel, Switzerland)
|October 16, 2025
概括
这项研究引入了一种新的三眼立体视觉系统,用于准确地定位行人. 该框架增强了深度估计,并实现实时性能,优于现有的双眼镜方法.
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
- 传感器融合式传感器
背景情况:
- 对于智能户外系统来说,行人定位至关重要.
- 传统的双眼立体视觉方法在准确性和效率方面存在局限性.
- 需要先进的传感器来实现可靠的户外导航和安全.
研究的目的:
- 使用三眼立体视觉开发一个改进的行人定位系统.
- 与双眼方法相比,提高深度估计的准确性和处理效率.
- 在户外环境中实现实时行人检测和跟踪.
主要方法:
- 一个三眼相机配置在一个等边三角设置为互补的视角.
- 整合多尺度模板匹配用于初始深度估计.
- 强制执行三视图几何一致性,用于精细的深度估计.
- 与YOLOv8-s探测器相结合,用于对象检测和定位.
主要成果:
- 获得了0.435m的平均绝对误差,用于行人深度估计.
- 每个目标的平均处理时间为3.13毫秒,超过了双眼方法.
- 实时运行>30Hz,端到端延迟为~32.56ms,最多可用于9名行人.
结论:
- 拟议的三眼立体视觉框架显著提高了行人定位的准确性和效率.
- 该系统为实时户外智能系统提供了强大的解决方案.
- 这种方法为增强的自主导航和安全系统提供了基础.
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