This project investigates bias in automatic facial recognition (FR). Specifically, subjects are grouped into predefined subgroups based on gender, ethnicity, and age. We propose a novel image collection called Balanced Faces in the Wild (BFW), which is balanced across eight subgroups (i.e., 800 face images of 100 subjects, each with 25 face samples).

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To study the driver's behavior in real traffic situations, we conducted experiments using an instrumented vehicle, which comprises:

(i) a camera, installed above the vehicle's side window and oriented toward the driver, and (ii) a Mobile Digital Video Recorder (MDVR).

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