通过深度学习,在前座乘客座椅上检测孩子的脸部
Carlos Hernández-Aguilar1, José A Aguilar-Saguilan1, Alejandro I Trejo-Castro2
1Escuela de Ingeniería y Tecnologías, Universidad de Monterrey, San Pedro Garza García, México.
Traffic injury prevention
|May 8, 2024
概括
车祸是年轻人死亡的主要原因之一. 一个新的儿童面部检测系统提醒驾驶员如果有一个孩子坐在前座,防止死亡事故的安全气囊部署.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 汽车安全 汽车安全
背景情况:
- 在全球范围内,道路交通事故是年轻人死亡的主要原因.
- 在正面碰撞中,安全气囊的部署对坐在前座乘客座位上的儿童构成致命的风险,特别是13岁以下的儿童.
研究的目的:
- 开发和评估一个利用儿童面部检测的室内监控系统,以减轻儿童在车祸中死亡的风险.
- 提高驾驶员对允许儿童坐在前座乘客座位上的危险的认识.
主要方法:
- 该系统采用深度学习技术,包括转移学习,微调和面部检测,用于强大的儿童识别.
- 为培训创建了一个定制的数据集,并选择了MobileNetV2架构,因为它的性能和低计算成本,使得它能够在Raspberry Pi 4B上实现.
- 使用数据增强技术来扩展数据集,最终得到了2,496张成人和2,310张儿童图像.
主要成果:
- 该系统在没有滑窗的情况下实现了98%的准确性和面部分类100%的精度.
- 实时检测前乘客座椅上的儿童,每次决定延迟1秒,达到100%的准确性.
- 开发的系统在识别前座儿童时表现出了强大的性能.
结论:
- 这项研究表明,在汽车中使用Raspberry Pi 4 Model B上的深度学习来实现一个强大的,非侵入性的儿童检测系统的可行性.
- 虽然实验准确度为100%,但实际情况如阳光和碎片可能会影响性能.
- 该系统提供了一种潜在的解决方案,通过防止前排座位的放置来提高车辆中的儿童安全.
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