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Gerçek Zamanlı Göz Bebeği Takip Sistemi İçin Hibrit Algoritma Geliştirilmesi

Year 2023, Volume: 8 Issue: 2, 114 - 130, 08.12.2023

Cumali Kara Gürkan Bilgin Süleyman Bilgin

Abstract

Farklı rahatsızlıkları nedeniyle kısıtlı motor becerilerine sahip, hareket yeteneği yetersiz, çevresi ile etkileşiminde sıkıntı bulunan kullanıcılar için göz takip sistemlerinin kullanımı önemlidir. Gerçekleştirilen bu çalışmada bu tür hastalığı olan kişilerin göz bebeği takibi ile sağladığı etkileşimin hassaslığı ve gücünü kullanarak bilgisayar erişimine yardımcı göz takip algoritması tasarlamak hedeflenmiştir. Motivasyonun sağlanmasında, günümüzdeki sistemlerin, göz bebeği takibi için kızılötesi görüntü algılama sistemlerine ihtiyaç duyması ve bunun gibi gereksinimlerin ek maliyetlere sebebiyet vermesi, bunun yerine taşınabilir kameralı bilgisayarlar üzerinden yazılacak bir algoritma ile takibin yapılması fikri etkili olmuştur. Ayrıca daha önce çalışılmış algoritmalara ilaveten yeni bir göz takip algoritması geliştirilmiştir. Ortaya konulan bu araştırma çalışmasında göz bölgesini tespit edebilmek için, Korelasyon ve Viola-Jones (VJ) algoritmaları birlikte kullanılarak hibrit VJVK (Viola-Jones ve Korelasyon) modeli oluşturulmuştur. VJVK ve VJ sonuçlarındaki farklılıkların incelenebilmesi için iki model için de ayrı ayrı göz bölgesi çalışmaları yapılmıştır. Farklı ışık ve mesafelerde denemeler gerçekleştirilerek algoritmaların performansları değerlendirilmiştir. VJVK ile VJ arasındaki fark hız ve doğrulukta yüzdelik olarak karşılaştırılmıştır. Ayrıca gerçek zamanlı göz bebeğini takip edebilecek sistem yeni oluşturulan VJVK ile gerçekleştirilmiştir.

Keywords

Görüntü İşleme Göz Takip Korelasyon Viola-Jones

References

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  • A. Gupta and R. Tiwari. "Face detection using modified Viola jones algorithm." International Journal of Recent Research in Mathematics Computer Science and Information Technology vol. 1.2, pp. 59-66, 2015.
  • R. Lienhart and J. Maydt, "An extended set of haar-like features for rapid object detection." Proceedings. international conference on image processing. Vol. 1. IEEE, 2002.
  • A. Çelik and E. Tekin, "Hough transform görüntü işleme yöntemiyle ekim makineleri için tohum sayma uygulaması," Avrupa Bilim ve Teknoloji Dergisi (2020), pp. 260-267, 2020.
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Year 2023, Volume: 8 Issue: 2, 114 - 130, 08.12.2023

Cumali Kara Gürkan Bilgin Süleyman Bilgin

Abstract

References

  • S. Metlek and H. Çetiner, "ResUNet+: A New Convolutional and Attention Block-Based Approach for Brain Tumor Segmentation." IEEE Access, 2023.
  • S. Metlek, "Forecasting of Dow Jones Sukuk Index Prices Using Artificial Intelligence Systems." Economic Computation & Economic Cybernetics Studies & Research, vol. pp.1, 2022.
  • O. Oral and G. Bilgin, “The Automatic Detection of Tomatoes Leaf Diseases.” Fresanieus Environmental Bulletin, vol. 30, pp. 4, 2021.
  • E. Çetin, S. Bilgin and G. Bilgin, "A novel wearable ERP-based BCI approach to explicate hunger necessity." Neuroscience Letters, 137573, 2023.
  • A. A. Elngar, M. Arafa, A. Fathy,B. Moustafa,O. Mahmoud, M. Shaban and N. Fawzy, "Image classification based on CNN: a survey," Journal of Cybersecurity and Information Management, vol. 6.1, pp. 18-50, April 2021.
  • A. Borji and I.Laurent, "State-of-the-art in visual attention modeling," IEEE transactions on pattern analysis and machine intelligence, vol. 35.1, pp. 185-207, 2012.
  • P. Smith, S. Mubarak and N. V. Lobo. "Determining driver visual attention with one camera," IEEE transactions on intelligent transportation systems, vol. 4.4, pp. 205-218, 2003.
  • A. Doshi and M. M. Trivedi, "On the roles of eye gaze and head dynamics in predicting driver's intent to change lanes," IEEE Transactions on Intelligent Transportation Systems, vol. 10.3, pp. 453-462, 2009.
  • H. Wang,C. Xue and Q. Liu. "The eye movement experiment and the usability evaluation of the fighter cockpit digital interface." in 2nd Int. Conf. on Information Engineering and Computer Science. IEEE, 2010, pp.1-4.
  • G. J. Siegle, S. R. Steinhauer, and M. E. Thase. "Pupillary assessment and computational modeling of the Stroop task in depression." International Journal of Psychophysiology, vol. 52.1, pp. 63-76, 2004.
  • V. Mylius, H. J. Braune and K. Schepelmann. "Dysfunction of the pupillary light reflex following migraine headache," Clinical Autonomic Research vol. 13, pp. 16-21, 203.
  • C. S. Hwang, H. H. Weng, L. F. Wang, C. H. Tsai and H. T. Chang, "An eye-tracking assistive device improves the quality of life for ALS patients and reduces the caregivers’ burden," Journal of motor behavior, vol. 46.4, pp. 233-238, 2014.
  • P. S. Holzman, R. P. Leonard and L. L. Deborah, et al., "Eye-tracking dysfunctions in schizophrenic patients and their relatives," Archives of general psychiatry vol. 31.2, pp. 143-151, 1974.
  • A. Kaya,A. B. Can and H. B. Çakmak, "Designing a pattern stabilization method using scleral blood vessels for laser eye surgery." 2010 20th Int. Conf. on Pattern Recognition. IEEE, 2010, pp. 698-701.
  • T. Brandt, Augenbewegungsstörungen: Klinik und Elektronystagmographie; 23 Tabellen. Fischer, 1983.
  • Y. Durna and A. Fikret, "Design of a binocular pupil and gaze point detection system utilizing high definition images." Applied Sciences vol. 7.5, pp. 498, 2017.
  • D. W. Hansen, and R. I. Hammoud, "An improved likelihood model for eye tracking," Computer Vision and Image Understanding, vol. 106, pp. 2-3, 2007.
  • J. C. Mateo, J. San Agustin and J. P. Hansen, "Gaze beats mouse: hands-free selection by combining gaze and emg." CHI'08 extended abstracts on Human factors in computing systems. pp. 3039-3044, 2008.
  • T. N. Bhaskar, F. T. Keat, S. Ranganath and Y. V. Venkatesh, "Blink detection and eye tracking for eye localization." TENCON 2003. Conf. on Convergent Technologies for Asia-Pacific Region. vol. 2, 2003.
  • B. Fatima, A. R. Shaid, S. Ziauddin, A. A. Safi and H. Ramzan, "Driver fatigue detection using viola jones and principal component analysis," Applied Artificial Intelligence, vol. 34.6, pp. 456-483, 2020.
  • M. Everingham and A. Zisserman. "Regression and classification approaches to eye localization in face images." 7th Int. Conf. on Automatic Face and Gesture Recognition (FGR06). IEEE, 2006.
  • P. Viola and M. J. Jones. "Robust real-time face detection." International journal of computer vision, vol. 57, pp. 137-154, 2004.
  • Y, Hua, J. Ni and H. Lu, "An eye-tracking technology and MLP-based color matching design method." Scientific Reports, vol. 13.1, pp. 1294, 2023.
  • D. B. Arslan, M. Sükuti and A. D. Duru, "The Identification of Individualized Eye Tracking Metrics in VR Using Data Driven Iterative-Adaptive Algorithm." AJIT-e: Academic Journal of Information Technology, vol. 14.52, pp. 8-21, 2023.
  • S. H. Z. Bagherzadeh and S. Toosizadeh, "Eye tracking algorithm based on multi model Kalman filter." HighTech and Innovation Journal, vol. 3.1, pp.15-27, 2022.
  • M. R. Kanhirakadavath and M. S. M. Chandran. "Investigation of eye-tracking scan path as a biomarker for autism screening using machine learning algorithms" Diagnostics, vol. 12.2, pp. 518, 2022.
  • Z. M. Fadhel and Q. M. Hussein, "Detecting autism spectrum disorder in children using eye tracking and machine learning." 2022 Int. Cong. on Human-Computer Interaction, Optimization and Robotic Applications (HORA), IEEE, 2022, pp.1-3. H. H. Tesfamikael, A. Fray, I. Mengsteab, A. Semere and Z. Amanuel, "Simulation of eye tracking control based electric wheelchair construction by image segmentation algorithm." Journal of Innovative Image Processing (JIIP), vol. 3.01, pp. 21-35, 2021.
  • F. N. Ibrahim, Z. M. Zin and N. Ibrahim, "Eye Feature Extraction with Calibration Model using Viola-Jones and Neural Network Algorithms." Advances in Science, Technology and Engineering Systems Journal, vol. 4.6, pp. 208-215, 2019.
  • G. Ananthi, M. Pujaa and V. M. Amretha. "Eye gaze capture for preference tracking." Multimedia Tools and Applications, vol. 1, pp. 12, 2023.
  • M. Jones, "Rapid Object Detection using a Boosted Cascade of Simple," Proceedings of the IEEE Computer Society Conf. on Computer Vision and Pattern Recognition, Kauai, HI, USA. IEEE, 2001, pp 8-14.
  • A. Gupta and R. Tiwari. "Face detection using modified Viola jones algorithm." International Journal of Recent Research in Mathematics Computer Science and Information Technology vol. 1.2, pp. 59-66, 2015.
  • R. Lienhart and J. Maydt, "An extended set of haar-like features for rapid object detection." Proceedings. international conference on image processing. Vol. 1. IEEE, 2002.
  • A. Çelik and E. Tekin, "Hough transform görüntü işleme yöntemiyle ekim makineleri için tohum sayma uygulaması," Avrupa Bilim ve Teknoloji Dergisi (2020), pp. 260-267, 2020.
  • D. H. Ballard, "Generalizing the Hough transform to detect arbitrary shapes," Pattern recognition, vol. 13.2, pp. 111-122, 1981.
  • A. Çubukçu, M. Kuncan and M. İmren, et al, "Görüntü işleme ile 3 eksenli robot mekanizması üzerinde nesne ayırt edilmesi ve sıralanması," 2015.
There are 35 citations in total.

Details

Primary Language Turkish
Subjects Artificial Intelligence (Other)
Journal Section articles
Authors

Cumali Kara 0000-0003-2291-1983

Gürkan Bilgin

Süleyman Bilgin 0000-0003-0496-8943

Publication Date December 8, 2023
Submission Date November 23, 2023
Acceptance Date December 7, 2023
Published in Issue Year 2023 Volume: 8 Issue: 2

Cite

IEEE C. Kara, G. Bilgin, and S. Bilgin, “Gerçek Zamanlı Göz Bebeği Takip Sistemi İçin Hibrit Algoritma Geliştirilmesi”, Yekarum, vol. 8, no. 2, pp. 114–130, 2023.
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