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一个实时的车辆安全系统,通过同步的物体检测和头部姿势估计通过立体视觉视觉

Julio C Rodriguez-Quiñonez¹, Jonathan J Sanchez-Castro¹, Oscar Real-Moreno¹

¹Universidad Autónoma de Baja California, Facultad de Ingeniería, Blvd. Benito Juárez S/N, 21280, Mexicali, Baja California, Mexico.

|September 3, 2024

概括

这项研究引入了一种先进的驾驶辅助系统 (ADAS),通过监控驾驶员的注意力和物体距离,以防止在低速区域发生事故. 该系统使用头部姿势估计和物体检测来确保足够的制动时间.

科学领域:

汽车工程汽车工程
计算机视觉计算机视觉
人工智能的人工智能

背景情况:

交通事故经常发生在低速度的城市环境中,如学校区和停车场.
现有的先进驾驶辅助系统 (ADAS) 可以加强,以提高这些领域的安全性.

研究的目的:

开发一种新的ADAS,分析驾驶员的注意力和物体距离,以减轻低速区域中的碰撞.
整合头部姿势估计 (HPE) 和物体/行人检测以进行实时风险评估.

主要方法:

利用头部姿势估计 (HPE) 的立体视觉计算欧勒角度,通过神经网络对驾驶员的注意力进行分类.
使用YOLO-R和SoRA模板匹配技术的立体视觉,用于准确和高效的物体/行人检测和距离计算.
集成HPE和物体检测,为危险场景提供及时警告.

主要成果:

在欧勒角计算中实现了低平均误差,以可靠地评估驾驶员的注意力.
使用YOLO-R和SoRA证明了高效的对象检测和距离测量,从而缩短了处理时间.
成功开发了一个集成的ADAS系统,能够分析驾驶员的注意力和对象的接近.

结论:

拟议的ADAS通过考虑驾驶员的注意力和物体距离,有效地提高了低速区域的安全性.
同时的HPE和物体检测提供了一个强大的框架来防止车辆事故.
该系统确保足够的制动时间,有助于减少道路碰撞.

关键词:

驾驶员的姿势分类驾驶员的姿势分类估计头部姿势的估计.里程碑检测检测地标的检测对象检测检测对象检测对象检测立体视觉视觉是什么

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