Electronics and Telecommunications Research Institute, 22, Daewangpangyo-ro 712beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do, Republic of Korea.
Department of Image, Chung-Ang University, 84 Heukseok-ro, Seoul, 06974, Korea.
Sci Rep. 2023 Oct 25;13(1):18264. doi: 10.1038/s41598-023-44955-1.
This paper introduces a real-time Driver Monitoring System (DMS) designed to monitor driver behavior while driving, employing facial landmark estimation-based behavior recognition. The system utilizes an infrared (IR) camera to capture and analyze video data. Through facial landmark estimation, crucial information about the driver's head posture and eye area is extracted from the detected facial region, obtained via face detection. The proposed method consists of two distinct modules, each focused on recognizing specific behaviors. The first module employs head pose analysis to detect instances of inattention. By monitoring the driver's head movements along the horizontal and vertical axes, this module assesses the driver's attention level. The second module implements an eye-closure recognition filter to identify instances of drowsiness. Depending on the continuity of eye closures, the system categorizes them as either occasional drowsiness or sustained drowsiness. The advantages of the proposed method lie in its efficiency and real-time capabilities, as it solely relies on IR camera video for computation and analysis. To assess its performance, the system underwent evaluation using IR-Datasets, demonstrating its effectiveness in monitoring and recognizing driver behavior accurately. The presented real-time Driver Monitoring System with facial landmark-based behavior recognition offers a practical and robust approach to enhance driver safety and alertness during their journeys.
本文介绍了一种实时驾驶员监控系统 (DMS)，该系统旨在监控驾驶员在驾驶过程中的行为，采用基于面部地标估计的行为识别。该系统使用红外 (IR) 摄像机来捕获和分析视频数据。通过面部地标估计，从通过面部检测获得的检测到的面部区域中提取驾驶员头部姿势和眼睛区域的关键信息。所提出的方法由两个不同的模块组成，每个模块都专注于识别特定的行为。第一个模块采用头部姿势分析来检测不注意的情况。通过监测驾驶员在水平和垂直轴上的头部运动，该模块评估驾驶员的注意力水平。第二个模块实现了闭眼识别滤波器，以识别困倦的情况。根据闭眼的连续性，系统将其分类为偶尔困倦或持续困倦。该方法的优点在于其效率和实时能力，因为它仅依靠 IR 摄像机视频进行计算和分析。为了评估其性能，该系统使用 IR-Datasets 进行了评估，证明了其在准确监控和识别驾驶员行为方面的有效性。本文提出的基于面部地标估计的实时驾驶员监控系统为提高驾驶员在行驶过程中的安全性和警觉性提供了一种实用且强大的方法。
