NADS-Net: A Nimble Architecture for Driver and Seat Belt Detection via Convolutional Neural Networks
A new convolutional neural network (CNN) architecture for 2D driver/passenger pose estimation and seat belt detection is proposed in this paper. The new architecture is more nimble and thus more suitable for in-vehicle monitoring tasks compared to other generic pose estimation algorithms. The new architecture, named NADS-Net, utilizes the feature pyramid network (FPN) backbone with multiple detection heads to achieve the optimal performance for driver/passenger state detection tasks. The new architecture is validated on a new data set containing video clips of 100 drivers in 50 driving sessions that are collected for this study. The detection performance is analyzed under different demographic, appearance, and illumination conditions. The results presented in this paper may provide meaningful insights for the autonomous driving research community and automotive industry for future algorithm development and data collection.
Code (0)
등록된 구현이 없습니다.
Tasks
Autonomous DrivingPose EstimationSimilar Papers 제목 키워드 기반
Robust Seatbelt Detection and Usage Recognition for Driver Monitoring Systems
Wearing a seatbelt appropriately while driving can reduce serious crash-related injuries or deaths by about half. However, current seatbelt reminder system has multiple shortcomings, such as can be easily fooled by a "Se…
Integrated In-vehicle Monitoring System Using 3D Human Pose Estimation and Seat Belt Segmentation
Recently, along with interest in autonomous vehicles, the importance of monitoring systems for both drivers and passengers inside vehicles has been increasing. This paper proposes a novel in-vehicle monitoring system the…
3D Human Pose Estimation3D Pose EstimationAutonomous VehiclesPose Estimation+1Neuromorphic Seatbelt State Detection for In-Cabin Monitoring with Event Cameras
Neuromorphic vision sensors, or event cameras, differ from conventional cameras in that they do not capture images at a specified rate. Instead, they asynchronously log local brightness changes at each pixel. As a result…
Binary ClassificationIdentifying roadway departure crash patterns on rural two-lane highways under different lighting conditions: association knowledge using data mining approach
More than half of all fatalities on U.S. highways occur due to roadway departure (RwD) each year. Previous research has explored various risk factors that contribute to RwD crashes, however, a comprehensive investigation…
Female and Combined Male-Female Injury Risk Functions for the Anterior Pelvis Under Frontal Lap Belt Loading Conditions
Purpose: Iliac wing fractures due to lap belt loading have been observed in laboratory settings for 50 years and recent data suggest they are also occurring in the field. Automated driving systems (ADS) and other occupan…