Driver performance detection & recommender system in vehicular environment using video streaming analytics

This tutorial deals with how the overall human performance while working can be detected, under different conditions and scenarios. The tutorial will talk about how regular and real-time monitoring of people can be carried out through eye-tracking and how it can be integrated with other environment factors to develop a recommender system. Particularly, the speakers would articulate a vehicular driving scenario and explain how a combined use of eye-tracking and face-tracking can not only help the drivers but also significantly assist in reducing the road accidents, thereby increase the road safety. Finally, the speakers will present the use of existing eye-trackers along with the integrated eye-tracker and face-tracker that is under indigenous development. This tutorial is intended for a wide section of audience - ranging from clusters of automobile designers/manufacturers, researchers in mechatronics and students researching on different aspects of connected cars, computer vision, signal processing, image processing and machine learning and data analytics.