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Volume: 31 | Article ID: art00010
Through the windshield driver recognition
  DOI :  10.2352/ISSN.2470-1173.2019.13.COIMG-140  Published OnlineJanuary 2019

Biometric recognition of vehicle occupants in unconstrained environments is rife with a host of challenges. In particular, the complications arising from imaging through vehicle windshields provide a significant hurdle. Distance to target, glare, poor lighting, head pose of occupants, and speed of vehicle are some of the challenges. We explore the construction of a multi-unit computational camera system to mitigate these challenges in order to obtain accurate and consistent face recognition results. This paper documents the hardware components and software design of the computational imaging system. Also, we document the use of Region-based Convolutional Neural Network (RCNN) for face detection and Generative Adversarial Network (GAN) for machine learning-inspired High Dynamic Range Imaging, artifact removal, and image fusion.

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David Cornett, Alec Yen, Grace Nayola, Diane Montez, Christi R. Johnson, Seth T. Baird, Hector Santos-Villalobos, David S. Bolme, "Through the windshield driver recognitionin Proc. IS&T Int’l. Symp. on Electronic Imaging: Computational Imaging XVII,  2019,  pp 140-1 - 140-9,

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