Improved Smart Eye Tracker Communicator Using Low Resolution Webcam
Resumo
Eye tracking is a tool presented in many applications ranging from scientific research to commercial applications. One of them is assistive technologies that aim to help people with some disabilities, including communication. However, the applications usually require specific hardware components or a high computational cost. This work proposes the Smart Eye Communicator II (SEC-II), an evolution of a previously presented algorithm to detect the pupil center and the user's gaze direction in real-time, using a low-resolution webcam and a conventional computer without a need for calibration. In SEC-II, a face aligner, which gets a canonical face alignment based on translation, scale, and rotation, has been added to the system. Likewise, strategies using eye coordinates were implemented to find the dominant the algorithm eye. By implementing these new approaches, achieved 86% accuracy, even under variable and non-uniform environmental conditions. Moreover, a graphical interface was implemented connecting the SEC-II to the internet and allowing users to express their desires and watch online videos chosen by themselves.Referências
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A. T. Duchowski and A. T. Duchowski, Eye tracking methodology: Theory and practice. Springer, 2017.
W. Chareonsuk, S. Kanhaun, K. Khawkam, and D. Wongsawang, “Face and Eyes mouse for ALS Patients,” in 2016 Fifth ICT International Student Project Conference (ICT-ISPC). IEEE, may 2016, pp. 77–80. [Online]. Available: http://ieeexplore.ieee.org/document/7519240/
P. S. Holzman, L. R. Proctor, D. L. Levy, N. J. Yasillo, H. Y. Meltzer, and S. W. Hurt, “Eye-tracking dysfunctions in schizophrenic patients and their relatives,” Archives of general psychiatry, vol. 31, no. 2, pp. 143–151, 1974.
M. Arbesman and K. Sheard, “Systematic Review of the Effectiveness of Occupational Therapy-Related Interventions for People With Amyotrophic Lateral Sclerosis,” American Journal of Occupational Therapy, vol. 68, no. 1, pp. 20–26, jan 2014. [Online]. Available: http://ajot.aota.org/Article.aspx?doi=10.5014/ajot.2014.008649
H. M. Elahi, D. Islam, I. Ahmed, S. Kobashi, and M. A. R. Ahad, “Webcam-based accurate eye-central localization,” Proceedings - 2013 2nd International Conference on Robot, Vision and Signal Processing, RVSP 2013, pp. 47–50, 2013.
J. R. Khonglah and A. Khosla, “A low cost webcam based eye tracker for communicating through the eyes of young children with ASD,” Proceedings on 2015 1st International Conference on Next Generation Computing Technologies, NGCT 2015, no. September, pp. 925–928, 2016.
R. Kaushik, T. Arora, Sukanya, and R. Tripathi, “Design of Eyewriter for ALS Patients through Eyecan,” in 2018 International Conference on Advances in Computing, Communication Control and Networking (ICACCCN). IEEE, oct 2018, pp. 991–995. [Online]. Available: https://ieeexplore.ieee.org/document/8748520/
A. L. d. S. Rocha, L. H. d. S. Silva, and B. J. Fernandes, “Eye-tracking algorithm for low webcam image resolution without calibration,” in Anais Estendidos do XXXIII Conference on Graphics, Patterns and Images. SBC, 2020, pp. 187–190.
D. L. Baggio, Mastering OpenCV with practical computer vision projects. Packt Publishing Ltd, 2012.
A. R. Martin, R. Reddy, and M. G. Fehlings, “Dropped head syndrome: diagnosis and management,” Evidence-based spine-care journal, vol. 2, no. 02, pp. 41–47, 2011.
Publicado
18/10/2021
Como Citar
ROCHA, Allana L. dos S.; SILVA, Leandro H. de S.; FERNANDES, Bruno J. T..
Improved Smart Eye Tracker Communicator Using Low Resolution Webcam. In: WORKSHOP DE TRABALHOS DA GRADUAÇÃO - CONFERENCE ON GRAPHICS, PATTERNS AND IMAGES (SIBGRAPI), 34. , 2021, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
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p. 218-222.
DOI: https://doi.org/10.5753/sibgrapi.est.2021.20042.