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Single-Chip Eye Tracker Using Smart CMOS Image Sensor Pixels

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Abstract

The eye tracker is a system that detects the point where the user gazes on. The conventional eye tracker using a Charge-Coupled Device (CCD) camera needs many peripherals and software computation causing high cost, computation time and power consumption. This paper proposes a single-chip eye tracker using smart CMOS Image Sensor (CIS) pixels. The proposed eye tracker does not require additional peripherals and operates at higher speed than the conventional approach. The prototype chip was designed and fabricated for a 32 × 32 smart CIS pixels array with a 0.35-μ m CMOS process. The test results show ± 1 pixel error at the rate of 125 frame-per-second. The power consumption is 260 mW with 3.3 V supply voltage and the silicon area is 3.8 mm2

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References

  1. T. Miyoshi and A. Murata, “Input device using eye tracker in human-computer interaction,” in Proc. 10th IEEE Int. Workshop Robot and Human Interactive Communication, Sept. 2001, pp. 18–21.

  2. G. Beach, C.J. Cohen, J. Braun, and G. Moody, “Eye tracker system for use with head mounted displays,” in IEEE Int. Conf. Systems, Man, and Cybernetics, vol. 5, pp. 4348–4352, Oct. 1998.

    Google Scholar 

  3. K. Iwamoto, S. Katsumata, and K. Tanie, “An eye movement tracking type head mounted display for virtual reality system: evaluation experiments of a prototype system,” in IEEE Int. Conf. Systems, Man, and Cybernetics, vol. 1, pp. 13–18, Oct. 1994.

  4. Z. Zhiwei, J. Qiang, K. Fujimura, and L. Kuangchih, “Combining Kalman filtering and mean shift for real time eye tracking under active IR illumination,” in Proc. 16th Int. Conf. Pattern Recognition, vol. 4, 2002, pp. 318–321.

    Google Scholar 

  5. T. Oya, H. Hashimoto, and F. Harashima, “Active eye sensing system-predictive filtering for visual tracking,” in Proc. Int. Conf. Industrial Electronics, Control, and Instrumentation, vol. 3, Nov. 1993, pp. 1718–1723.

  6. A. Graupner, J. Schreiter, S. Getzlaff, and R. Schüffny, “CMOS image sensor with mixed-signal processor array.” IEEE J. Solid-State Circuits, vol. 38, pp. 948–957, 2003.

    Article  Google Scholar 

  7. Y. Muramatsu, S. Kurosawa, M. Furumiya, H. Ohkubo, and Y. Nakashiba, “A signal-processing CMOS image sensor using a simple analog operation.” IEEE J. Solid-State Circuits, vol. 38, pp. 101–106, 2003.

    Article  Google Scholar 

  8. M. Schanz, W. Brochherde, R. Hauschild, B. J. Hosticka, and M. Schwarz, “Smart CMOS image sensor arrays.” IEEE Trans. Electron Devices, vol. 44, pp. 1699–1705, Oct. 1997.

    Article  Google Scholar 

  9. Y. Ni and J. Guan, “A 256 × 256 pixel smart CMOS image sensor for line-based stereo vision applications.” IEEE J. Solid-State Circuits, vol. 35, pp. 1055–1061, 2000.

    Article  Google Scholar 

  10. S. Espejo, A. Rodríguez-Vázquez, R. Domínguez-Castro, J. L. Huertas, and E. Sánchez-Sinencio, “Smart-pixel cellular neural networks in analog current-mode CMOS technology.” IEEE J. Solid-State Circuits, vol. 29, pp. 895–905, 1994.

    Article  Google Scholar 

  11. M. Schwarz, R. Hauschild, B. J. Hosticka, J. Huppertz, T. Kneip, S. Kolnsberg, L. Ewe, and H. K. Trieu, “Single-chip CMOS image sensors for a retina implant system.” IEEE Trans. Circuits Syst. vol. 46, pp. 870–877, 1999.

    Article  Google Scholar 

  12. L. O. Chua and L. Yang, “Cellular neural networks: theory.” IEEE Trans. Circuits Syst., vol. 35, pp. 1257–1272, 1988.

    Article  Google Scholar 

  13. L. O. Chua and L. Yang, “Cellular neural networks: applications.” IEEE Trans. Circuits Syst., vol. 35, pp. 1273–1290, 1988.

    Article  Google Scholar 

  14. A. Fish, D. Turchin, and O. Yadid-Pecht, “An APS with 2-D winner-take-all selection employing adaptive spatial filtering and false alarm reduction.” IEEE Trans. electron Devices, vol. 50, pp. 159–165, 2003.

    Article  Google Scholar 

  15. T. Serrano-Gotarredona and B. Linares-Barranco, “A high-precision current-mode WTA-MAX circuit with multichip capability.” IEEE J. Solid-State Circuits, vol. 33, pp. 280–286, 1998.

    Article  Google Scholar 

  16. I. E. Opris, “Analog rank extractors.” IEEE Trans. Circuits Syst., vol. 44, no. 12, pp. 1114–1121, 1997.

    Article  Google Scholar 

  17. J. Choi and B. J. Sheu, “A high-precision VLSI winner-take-all circuit for self-organizing neural networks.” IEEE J. Solid-State Circuits, vol. 28, no. 5, pp. 576–584, 1993.

    Article  Google Scholar 

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Correspondence to Dongsoo Kim.

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Kim, D., Lim, S. & Han, G. Single-Chip Eye Tracker Using Smart CMOS Image Sensor Pixels. Analog Integr Circ Sig Process 45, 131–141 (2005). https://doi.org/10.1007/s10470-005-4006-7

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  • DOI: https://doi.org/10.1007/s10470-005-4006-7

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