Driver face tracking using semantics-based feature of eyes on single FPGA

Ying-Hao Yu; Ji-An Chen; Yi-Siang Ting; Ngaiming Kwok

doi:10.1117/12.2280295

19 June 2017 Driver face tracking using semantics-based feature of eyes on single FPGA

Ying-Hao Yu, Ji-An Chen, Yi-Siang Ting, Ngaiming Kwok

Proceedings Volume 10443, Second International Workshop on Pattern Recognition; 104430F (2017) https://doi.org/10.1117/12.2280295
Event: Second International Workshop on Pattern Recognition, 2017, Singapore, Singapore

Abstract

Tracking driver’s face is one of the essentialities for driving safety control. This kind of system is usually designed with complicated algorithms to recognize driver’s face by means of powerful computers. The design problem is not only about detecting rate but also from parts damages under rigorous environments by vibration, heat, and humidity. A feasible strategy to counteract these damages is to integrate entire system into a single chip in order to achieve minimum installation dimension, weight, power consumption, and exposure to air. Meanwhile, an extraordinary methodology is also indispensable to overcome the dilemma of low-computing capability and real-time performance on a low-end chip. In this paper, a novel driver face tracking system is proposed by employing semantics-based vague image representation (SVIR) for minimum hardware resource usages on a FPGA, and the real-time performance is also guaranteed at the same time. Our experimental results have indicated that the proposed face tracking system is viable and promising for the smart car design in the future.

Citation Download Citation

Ying-Hao Yu, Ji-An Chen, Yi-Siang Ting, and Ngaiming Kwok "Driver face tracking using semantics-based feature of eyes on single FPGA", Proc. SPIE 10443, Second International Workshop on Pattern Recognition, 104430F (19 June 2017); https://doi.org/10.1117/12.2280295

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