基于面部图像分析的疲劳检测

F. Noronha, Leandro Luiz de Almeida, Francisco Assis da Silva, Flávio Pandur Albuquerque Cabral, Robson Augusto Siscoutto
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引用次数: 0

摘要

近年来,大量因疲劳引起的事故和伤害引起了人们的关注,越来越受到人们的重视。由于技术和计算机视觉的不断发展,研究和开发能够检测用户疲劳的技术已经成为可能。图像处理因为不干扰车辆的驾驶而成为一种强大的工具,然而,也有一些干扰使得通过计算机视觉对驾驶员进行分析变得困难,这些干扰由于涉及到环境的亮度、工具的计算能力成本以及环境中不必要的物体而难以控制。使用了计算机视觉技术:模板匹配,霍夫转换和地标,在OpenCV库的帮助下使用Python语言,并使用低成本的硬件,如Raspberry。结果令人满意,并表明技术和控制光的结合使得检测疲劳和提醒驾驶员具有很高的准确性成为可能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DETECÇÃO DE FADIGA A PARTIR DA ANÁLISE DE IMAGENS FACIAIS
A large number of accidents and injuries caused by the presence of fatigue on people has caused a concern about this, more attention has been taken in recent years. Studying and developing techniques capable of detecting fatigue in a user has become possible thanks to the continuous evolution of technology and computer vision. Image processing has become a strong tool because does not interfere the driving of the vehicle, however, there are interferences that make difficult the analysis of the driver through the computer vision, these interferences are difficult to control because they involve the luminosity of the environment, cost of computational power of the tool and unnecessary objects in the environment. computer vision techniques were used: Template Matching, Hough Transfor and Landmarks, Python language with the help of the OpenCV library and use of low cost hardware such as Raspberry. The results were satisfactory and show that the combination of techniques and controlled light makes it possible to detect fatigue and alert the driver with great accuracy.
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