| KEYWORD |
Face identification and body pose estimation for intelligent vehicle applications
Thesis in external company
keywords ARTIFICIAL INTELLIGENCE, BODY POSE RECOGNITION, COMPUTER VISION, FACE RECOGNITION, INTELLIGENT VEHICLES, MACHINE LEARNING
Reference persons FABRIZIO LAMBERTI
External reference persons Pandeli Borodani, Centro Ricerche Fiat (CRF)
Research Groups DAUIN - GR-09 - GRAphics and INtelligent Systems - GRAINS
Thesis type THESIS IN COLLAB. W/ A COMPANY, THESIS WITH A COMPANY
Description One of the challenges for future intelligent vehicle applications, will be to determine whether a person is authorized to operate the vehicle or not. The face is the most common identifier in humans. Face recognition is a biometric application to recognize and identify the facial patterns of the human faces. These facial patterns of persons are compared and extracted by their facial contours. Anyway, extraneous imaging components, for example, posture, light and outward appearance still reason much inconvenience in exact face acknowledgment.
Furthermore, if the problem of recognizing the owner of a vehicle moves outside the car itself, that is, the system must recognize the owner in exceptional access conditions, the problem becomes even more tough - recognition in the “wild”. It means to build a fast and accurate system that can detect, recognize, and verify the driver’s identity in presence of constraints introduced in the car environment in different lighting and other external conditions. Recently, human pose estimation is an important and widely concerned research topic in computer vision. Given an image or video input, 3D human pose estimation aims to predict the configuration of the human body. The use of body posture can contribute to biometric identification with a multimodal approach.
The focus of this thesis, developed in collaboration with Centro Ricerche Fiat (CRF) and Stellantis, will be on multimodal AI models, combining face identification with body pose estimation to tackle the above challenges.
See also http://grains.polito.it/work.php
Deadline 28/05/2024
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