Giuseppe Scarso
Face and gait fusion techniques for vehicle owner recognition.
Rel. Fabrizio Lamberti, Pandeli Borodani, Federico Boscolo. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Informatica (Computer Engineering), 2024
Abstract
Intelligent vehicle applications are transforming the landscape of automotive technology, offering advancements that enhance safety, security, and user experience. A critical aspect of these applications is the ability to accurately identify and authenticate the owner of the vehicle, ensuring that only authorized users can operate or interact with the vehicle's systems. The research developed in this thesis work is part of a larger initiative by Centro Ricerche Fiat (CRF) and Stellantis, which aims to develop cutting-edge security mechanisms for intelligent vehicles. Specifically, the study investigates the combination of face recognition and body pose estimation leveraging gait analysis to create a multimodal authentication system able to achieve robust and secure human authentication while approaching the vehicle from the outside.
This work specifically focuses on evaluating various advanced fusion techniques, including polynomial feature fusion, hierarchical feature fusion, approaches based on deep learning architectures and other approaches, comparing them with state-of-the-art results provided by previous studies involving score level fusion techniques
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