Distributed Real-Time Computation of the Point of Gaze

Authors

  • Antonio García Dopico Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Facultad de Informática, Universidad Politécnica de Madrid, E-28660, Boadilla del Monte, Madrid
  • José L. Pedraza Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Facultad de Informática, Universidad Politécnica de Madrid, E-28660, Boadilla del Monte, Madrid
  • M. Luisa Córdoba Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Facultad de Informática, Universidad Politécnica de Madrid, E-28660, Boadilla del Monte, Madrid
  • Francisco M. Sánchez Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Facultad de Informática, Universidad Politécnica de Madrid, E-28660, Boadilla del Monte, Madrid
  • Antonio Pérez Departamento de Arquitectura y Tecnología de Sistemas Informáticos, Facultad de Informática, Universidad Politécnica de Madrid, E-28660, Boadilla del Monte, Madrid

Keywords:

Eye-tracking, cluster computing, real time distributed applications, parallel image processing, MPI, embedded systems

Abstract

This paper presents a minimally intrusive real-time gaze-tracking prototype to be used in several scenarios, including a laboratory stall and an in-vehicle system. The system requires specific infrared illumination to allow it to work with variable light conditions. However, it is minimally intrusive due to the use of a carefully configured switched infrared LED array. Although the perceived level of illumination generated by this array is high, it is achieved using low-emission infrared light beams. Accuracy is achieved through a precise estimate of the center of the user's pupil. To overcome inherent time restrictions while using low-cost processors, its main image-processing algorithm has been distributed over four main computing tasks. This structure not only enables good performance, but also simplifies the task of experimenting with alternative computationally-complex algorithms and with alternative tracking models based on locating both user eyes and several cameras to improve user mobility.

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Published

2015-02-10

How to Cite

Dopico, A. G., Pedraza, J. L., Córdoba, M. L., Sánchez, F. M., & Pérez, A. (2015). Distributed Real-Time Computation of the Point of Gaze. COMPUTING AND INFORMATICS, 33(4), 735–756. Retrieved from https://www.cai.sk/ojs/index.php/cai/article/view/724