Abstract
In the automotive industry, researchers, AI experts, and developers are actively pushing deep learning based approaches for In-vehicle safety. In this research paper, we propose a hybrid deep learning based visual system for providing feedback to the driver in a non-intrusive manner. We describe a hybrid SSD-RBM (Single Shot MultiBox Detector - Restricted Boltzmann Machine) model for face feature identification. In this system, object detection, object tracking, and observations are processed through a full pipeline of image processing and detect the driver's movements and generate a safe and efficient action plan in real time. This in-vehicle interactive system assists drivers in regulating driving performance and avoiding hazards.
Highlights
A Hybrid Deep Learning Based Visual System for InVehicle SafetyAbstract—In the automotive industry, researchers, AI experts, and developers are actively pushing deep learning based approaches for In-vehicle safety
Global Status report on road safety in 2018, the number of road traffic deaths continues to rise steadily, reaching 1.35 million in 2016
The report further says that Vehicle safety is increasingly critical to the prevention of crashes and has been shown to contribute to substantial reductions in the number of deaths and serious injuries resulting from road traffic crashes. [1]
Summary
Abstract—In the automotive industry, researchers, AI experts, and developers are actively pushing deep learning based approaches for In-vehicle safety. We propose a hybrid deep learning based visual system for providing feedback to the driver in a non-intrusive manner. We describe a hybrid SSD-RBM model for face feature identification. In this system, object detection, object tracking, and observations are processed through a full pipeline of image processing and detect the driver's movements and generate a safe and efficient action plan in real time. Object detection, object tracking, and observations are processed through a full pipeline of image processing and detect the driver's movements and generate a safe and efficient action plan in real time This in-vehicle interactive system assists drivers in regulating driving performance and avoiding hazards
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