Emotion Based Safe Driving

Project Code :TCMAPY189

Objective

Studies have established that driver’s emotions plays an important role in driving behavior. Therefore, continuous monitoring of the driver’s emotions and requisite warning to the driver will help in maintaining safety on the roads. In this application, we propose a real time camera based emotion detection system using deep learning and AI to alert the driver.

Abstract

While driving in a car, the driver can be affected by various emotionally challenging situations. They can either be triggered by the current driving situation, e.g. being cut off by another driver, or caused by a personal event, e.g. receiving good news. On the one hand, emotions can affect the driving behavior in positive and negative ways.

By sensing fear, the driver is able to perceive a situation as a possible risk and adapt his driving towards the situation, while anger may lead to an underestimation of the risk level and therefore may increase the risk of causing an accident. In this application, we propose a framework for driver’s emotion recognition using facial expression recognition.

We assume that a camera is optimally placed inside a vehicle, constantly looking at the driver’s face. Our framework comprises of extracting features from real-time video input using deep learning and classifying the emotion using Grassmann manifold based learning.

Keywords: Driver Emotion Recognition, Facial Expression Recognition, Intelligent Vehicles, Grassmann Manifolds, Machine Learning, Computer Vision.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.