IEEE Access (Jan 2023)

A Resource-Efficient Multi-Function Embedded Eye Tracker System Implemented on FPGA

  • Ahmad Mouri Zadeh Khaki,
  • Sanghyeok Yang,
  • Hyunsoo Kim,
  • Ankur Singh,
  • Byung-Geun Lee

DOI
https://doi.org/10.1109/ACCESS.2023.3342839
Journal volume & issue
Vol. 11
pp. 142931 – 142939

Abstract

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In this paper, a multi-function embedded eye tracker system (ETS) has been presented and FPGA implementation of that has been described. The image processing algorithm is based on morphological operations to detect centers of pupil (PC) and corneal glint (GC) so that gaze of the user can be estimated by establishing a mapping between obtained PC-GC vector and screen. Moreover, the proposed ETS is capable to detect pupil size which is vitally important in understanding consciousness of the user since it varies in response to light condition. Taking advantage of optimum system design and parallel signal processing on high-speed digital units of the FPGA, the processing time of 1.8 ms was achieved that allows operation of the system up to 500 fps. The results of test with $176\times120$ images demonstrate maximum vertical or horizontal error of ±1 pixel. Experimental results imply versatility of the proposed low-power and high-accuracy ETS for real-time and accurate applications such as medical diagnosis and human-computer interface.

Keywords