Cascade Learning for Driver Facial Monitoring

Gou, Chao; Zhou, Yuchen; Xiao, Yao; Wang, Xiao; Yu, Hui

doi:10.1109/tiv.2022.3173397

Cited by 19 publications

(5 citation statements)

References 48 publications

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“…Authors in [15] proposed driver distraction detection using facial landmarks and head pose. Further, Chao et al [16] proposed a cascaded learning approach for driver facial monitoring. Kim et al [44] introduced a lightweight driver monitoring system based on Multi-Task MobileNets, which improved the accuracy of driver status recognition with resource sharing devices.…”

Section: A Driver Monitoring Systemsmentioning

confidence: 99%

Optimization of Event Camera Bias Settings for a Neuromorphic Driver Monitoring System

Dilmaghani,

Shariff,

Farooq

et al. 2024

IEEE Access

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Event cameras provide a novel imaging technology for high-speed analysis of localized facial motions such as eye gaze, eye-blink and micro-expressions by taking input at the level of an individual pixel. Due to this capability, and lightweight amount of the output data these cameras are being evaluated as a viable option for driver monitoring systems (DMS). This research investigates the impact of pixelbias alteration on DMS features, which are: face tracking, blink counting, head pose and gaze estimation. In order to do this, new metrics are proposed to evaluate how effectively the DMS performs for each feature and overall. These metrics identify stability as the most important factor for face tracking, head pose estimations, and gaze estimations. The accuracy of the blink counting, which is the key component of this function, is also evaluated. Finally, all of these metrics are used to assess the system's overall performance. The effects of bias changes on each feature are explored on a number of human subjects with their consent. The newly proposed metrics are used to determine the ideal bias ranges for each DMS feature and the overall performance. The results indicate that the DMS's functioning is enhanced with proper bias tuning based on the proposed metrics.

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Section: A Driver Monitoring Systemsmentioning

confidence: 99%

Optimization of Event Camera Bias Settings for a Neuromorphic Driver Monitoring System

Dilmaghani,

Shariff,

Farooq

et al. 2024

IEEE Access

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“…The virtual world is generally constructed through various simulation software and frameworks. According to the testing requirements and the necessary content for the virtual world in VIL, the prevalent simulation software in the market is divided into three distinct categories in this article: open-source frameworks based on game engines (e.g., CARLA and AirSim), [59,60] commercial software designed for ADAS functionality testing (such as PreScan, [61] CarSim, [62] CarMaker, [63] and etc. ), and traffic flow simulation software like SUMO and VISSIM.…”

Section: Testbench-based Vehicle-in-the-loop For Av Testingmentioning

confidence: 99%

A Survey on Testbench‐Based Vehicle‐in‐the‐Loop Simulation Testing for Autonomous Vehicles: Architecture, Principle, and Equipment

Cheng,

Wang,

Zhao

et al. 2024

Advanced Intelligent Systems

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Autonomous vehicles (AVs) must be thoroughly tested to ensure safety and reliability before marketing. Simulation‐based testing has gained widespread recognition as the essential approach for AV testing by providing sufficient testing scenarios in the virtual environment. Vehicle‐in‐the‐loop (VIL) simulation has the ability to perform comprehensive tests and validations for the AVs’ overall behaviors while keeping significant testing accuracy and efficiency through the combination of the virtual scenarios and the physical AV. This article provides an overview of representative studies on testbench‐based VIL simulation testing for AVs, mainly focusing on utilizing testbenches to simulate realistic road conditions, and using physical signal stimulation methods and related equipment to generate sensors’ physical signals. This article first summarizes current AV testing studies, identifying existing issues and flaws of the state‐of‐the‐art methods and tools. Afterward, the testbench‐based VIL is addressed around architecture, principles, advantages, and characteristics. Then, the road condition simulation and the sensor physical signal generation in VIL are discussed in depth from structure, principle, and corresponding advanced equipment. Finally, research gaps between cutting‐edge technologies and AV testing applications in industrialization are identified to facilitate future research in this direction.

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“…Given the growth of intelligent technologies in the past decades, researchers have studied the driver monitoring system (DMS) [51][52][53][54][55] from various perspectives, and related applications for advanced driver assistance systems (ADASs) have been proposed [56][57][58][59]. However, these studies primarily focused on a specific application or situation without a comprehensive perspective.…”

Section: Introductionmentioning

confidence: 99%

Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

Lou

Xing

et al. 2022

IEEE Trans. Intell. Veh.

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Digital Twin (DT) is an emerging technology and has been introduced into intelligent driving and transportation systems to digitize and synergize connected automated vehicles. However, existing studies focus on the design of the automated vehicle, whereas the digitization of the human driver, who plays an important role in driving, is largely ignored. Furthermore, previous driver-related tasks are limited to specific scenarios and have limited applicability. Thus, a novel concept of a driver digital twin (DDT) is proposed in this study to bridge the gap between existing automated driving systems and fully digitized ones and aid in the development of a complete driving human cyber-physical system (H-CPS). This concept is essential for constructing a harmonious human-centric intelligent driving system that considers the proactivity and sensitivity of the human driver. The primary characteristics of the DDT include multimodal state fusion, personalized modeling, and time variance. Compared with the original DT, the proposed DDT emphasizes on internal personality and capability with respect to the external physiological-level state. This study systematically illustrates the DDT and outlines its key enabling aspects. The related technologies are comprehensively reviewed and discussed with a view to improving them by leveraging the DDT. In addition, the potential applications and unsettled challenges are considered. This study aims to provide fundamental theoretical support to researchers in determining the future scope of the DDT system.

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Cascade Learning for Driver Facial Monitoring

Cited by 19 publications

References 48 publications

Optimization of Event Camera Bias Settings for a Neuromorphic Driver Monitoring System

Optimization of Event Camera Bias Settings for a Neuromorphic Driver Monitoring System

A Survey on Testbench‐Based Vehicle‐in‐the‐Loop Simulation Testing for Autonomous Vehicles: Architecture, Principle, and Equipment

Review and Perspectives on Driver Digital Twin and Its Enabling Technologies for Intelligent Vehicles

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