Chapter
Jul 2, 2019
Driver Identity Recognition Based on Curved Handprints on Steering Wheel
Authors: Dan Wu [email protected], Yang Li [email protected], Kai Zhang [email protected], and Yi Zhang [email protected]Author Affiliations
Publication: CICTP 2019
Abstract
Identity recognition of drivers is important for improving vehicle security and driving safety, especially in truck transportation. Continuous tracking of driver identity can prevent unauthorized drivers to take over the control of the truck, as well as detect whether drivers have changed shifts within their maximum allowed driving duration. The identification method also needs to be non-intrusive to reduce distractions for the driver. In this paper, we propose a system that analyzes real-time handprints on the steering wheel to recognize a driver’s identity. We present a novel mapping algorithm that matches planar handprints to curved ones. Then we use the matching result to perform identity recognition. We demonstrate this system using handprint data collected from 47 subjects. In addition, we analyze how feature matching of curved handprints are affected by the diameter of the steering wheel.
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© 2019 American Society of Civil Engineers.
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Published online: Jul 2, 2019
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Environmental Science and New Energy Technology Engineering Laboratory, Tsinghua–Berkeley Shenzhen Institute, Tsinghua Univ., Shenzhen 518055, P.R. China. E-mail: [email protected]
Environmental Science and New Energy Technology Engineering Laboratory, Tsinghua–Berkeley Shenzhen Institute, Tsinghua Univ., Shenzhen 518055, P.R. China. E-mail: [email protected]
Graduate School at Shenzhen, Tsinghua Univ., Tsinghua Campus, University Town, Shenzhen 518055, China. E-mail: [email protected]
Tsinghua–Berkeley Shenzhen Institute, Tower C2, Nanshan Intelligence Park 1001, Xueyuan Blvd., Nanshan District, Shenzhen 518055, China; Dept. of Automation, Tsinghua National Laboratory for Information Science and Technology, Tsinghua Univ., Beijing 100084, China; Graduate School at Shenzhen, Tsinghua Univ., Tsinghua Campus, University Town, Shenzhen 518055, China. E-mail: [email protected]
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