Real-Time Driver Monitoring for Driving Safety
Real-Time Driver Monitoring for Driving Safety
Real-Time Driver Monitoring for Driving Safety
Real-Time Driver Monitoring for Driving Safety
Organization:
My Heart & Soul
Organization:
My Heart & Soul
Organization:
My Heart & Soul
Duration:
Jun 2021 – Jan 2022
Duration:
Jun 2021 – Jan 2022
Duration:
Jun 2021 – Jan 2022
Overview
Built a model to recognize facial expressions of drivers, using CNN and mini_XCEPTION.
Investigated and simulated the impact of individual driver’s emotions on overall traffic conditions, using models summarized from existing literature and SUMO package.
Developed software that enables interactive control of the system, batch image processing, and real-time video monitoring; implemented result visualization and automated generation of daily emotion reports using Python libraries (e.g., NumPy, Pandas, Matplotlib, Seaborn).
Overview
Built a model to recognize facial expressions of drivers, using CNN and mini_XCEPTION.
Investigated and simulated the impact of individual driver’s emotions on overall traffic conditions, using models summarized from existing literature and SUMO package.
Developed software that enables interactive control of the system, batch image processing, and real-time video monitoring; implemented result visualization and automated generation of daily emotion reports using Python libraries (e.g., NumPy, Pandas, Matplotlib, Seaborn).
Overview
Built a model to recognize facial expressions of drivers, using CNN and mini_XCEPTION.
Investigated and simulated the impact of individual driver’s emotions on overall traffic conditions, using models summarized from existing literature and SUMO package.
Developed software that enables interactive control of the system, batch image processing, and real-time video monitoring; implemented result visualization and automated generation of daily emotion reports using Python libraries (e.g., NumPy, Pandas, Matplotlib, Seaborn).
Overview
Built a model to recognize facial expressions of drivers, using CNN and mini_XCEPTION.
Investigated and simulated the impact of individual driver’s emotions on overall traffic conditions, using models summarized from existing literature and SUMO package.
Developed software that enables interactive control of the system, batch image processing, and real-time video monitoring; implemented result visualization and automated generation of daily emotion reports using Python libraries (e.g., NumPy, Pandas, Matplotlib, Seaborn).
