A Novel Eye Gaze Estimation Method Using Ant Colony Optimizer
الموضوعات : Journal of Computer & Robotics
1 - Department of Computer Engineering, Amirkabir University of Technology, Tehran, Iran
الکلمات المفتاحية: Ant Colony Algorithm, Eye-Gaze Estimation, Low-Resolution Image, Kirsch Filter, 2D image,
ملخص المقالة :
This paper addresses the eye gaze estimation problem in low-resolution images, using the low-cost camera in order to eliminate problems caused by infrared high-resolution imaging such as needing an expensive camera, complex setup, special light sources, and being limited in lab research environments. In the proposed method, the human face is detected with Ant Colony Optimization (ACO) algorithm, and then the Kirsch compass mask is utilized to detect the position of humans’ eyes. For iris detection, a novel strategy based on ACO algorithm, which has been rarely used before, is applied. The pupil is recognized by morphological processing. Finally, the extracted features, obtained from the radius and position of the irises of the pupils, are given to the Support Vector Machine (SVM) classifier to detect the gaze pointing. In order to receive assurance of the reliability and superiority of the newly designed ACO algorithm, some other metaheuristic algorithms such as (GA, PSO, and BBO) are implemented and evaluated. Additionally, a novel dataset, comprising 700 images gazing at seven different major orientations, is created in this research. The extensive experiments are performed on three various datasets, including Eye-Chimera with 92.55% accuracy, BIOID dataset with 96% accuracy, and the newly constructed dataset with 90.71% accuracy. The suggested method outperformed the state of the art gaze estimation methods in terms of the robustness and accuracy.
[1] Kim, B. C.; Ko, D.; Jang, U.; Han, H.; Lee, E. C., 3D Gaze tracking by combining eye-and facial-gaze vectors. The Journal of Supercomputing, vol. 73, no. 7, pp. 3038-3052 (2017).
[2] Stanovich, K. E., "Concepts in developmental theories of reading skill: Cognitive resources, automaticity, and modularity" Developmental review, vol. 10, no. 1, pp. 72-100 (1990).
[3] Armato, A.; Lanatà, A.; Scilingo, E. P., "Comparative study on photometric normalization algorithms for an innovative, robust and real-time eye gaze tracker", Journal of real-time image processing, vol. 8, no. 1, pp. 21-33 (2013).
[4] Biswas, P.; Langdon, P., "Multimodal intelligent eye-gaze tracking system", International Journal of Human-Computer Interaction, vol. 31, no. 4, pp. 277-294 (2015).
[5] Chen, J.; Ji, Q., "A Probabilistic Approach to Online Eye Gaze Tracking Without Explicit Personal Calibration", IEEE Transactions On Image Processing, vol. 24, no. 3, pp. 1076-1086 (2015).
[6] Maheswari, S. U.; Anbalagan, P.; Priya, T., "Efficient iris recognition through improvement in iris segmentation algorithm", International Journal on Graphics, Vision and Image Processing, vol. 8, no. 2, pp. 29-35 (2008).
[7] Jagadeesan, A.; Thillaikkarasi, T.; Duraiswamy, K., "Cryptographic key generation from multiple biometric modalities: Fusing minutiae with iris feature", Int. J. Comput. Appl, vol. 2, no. 6, pp. 16-26 (2010).
[8] Krisshna, N. A.; Deepak, V. K.; Manikantan, K.; Ramachandran, S., "Face recognition using transform domain feature extraction and PSO-based feature selection", Applied Soft Computing, vol. 22, pp. 141-161 (2014).
[9] Tan, K. H.; Kriegman, D. J.; Ahuja, N., "Appearance-based eye gaze estimation", In Applications of Computer Vision, (WACV 2002). Proceedings. Sixth IEEE Workshop on pp. 191-195 IEEE (2002).
[10] Lu, F.; Okabe, T.; Sugano, Y.; Sato, Y., "A head pose-free approach for appearance-based gaze estimation", In BMVC, pp. 1-11 (2011) .
[11] Sugano, Y.; Matsushita, Y.; Sato, Y.; Koike, H., "An incremental learning method for unconstrained gaze estimation", In European Conference on Computer Vision, Springer, Berlin, Heidelberg, pp. 656-667 (2008).
[12] Kim, H.; Lee, S. H.; Sohn, M. K.; Kim, D. J., "Illumination invariant head pose estimation using random forests classifier and binary pattern run length matrix", Human-centric Computing and Information Sciences, vol. 4, no. 1 (2014).
[13] Simon, D., "Biogeography-based optimization", IEEE transactions on evolutionary computation, vol. 12, no. 6, pp. 702-713 (2008).
[14] Cho, D. C.; Yap, W. S.; Lee, H.; Lee, I.; Kim, W. Y., "Long range eye gaze tracking system for a large screen", IEEE Transactions on Consumer Electronics, vol. 58, no. 4 (2012).
[15] Bostanci, E.; Kanwal, N.; Clark, A. F., "Augmented reality applications for cultural heritage using Kinect", Human-centric Computing and Information Sciences, vol. 5, no. 1 (2015).
[16] Wang, J. G.; Sung, E., "Study on eye gaze estimation", IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), vol. 32, no. 3, pp. 332-350 (2002).
[17] Wang, J. G.; Sung, E.; Venkateswarlu, R., "Estimating the eye gaze from one eye", Computer Vision and Image Understanding, vol. 98, no. 1, pp. 83-103 (2005).
[18] Zhang, W.; Zhang, T. N.; Chang, S. J., "Eye gaze estimation from the elliptical features of one iris", Optical Engineering, vol. 50, no. 4 (2011).
[19] Eberhart, R.; Kennedy, J., "A new optimizer using particle swarm theory", In Micro Machine and Human Science, 1995. MHS'95, Proceedings of the Sixth International Symposium on (pp. 39-43). IEEE (1995).
[20] Valenti, R.; Gevers, T., "Accurate eye center location through invariant isocentric patterns", IEEE transactions on pattern analysis and machine intelligence, vol. 34, no. 9, pp. 1785-1798 (2012).
[21] Valenti, R.; Gevers, T., "Accurate eye center location and tracking using isophote curvature", In Computer Vision and Pattern Recognition, CVPR 2008. IEEE Conference on pp. 1-8 (2008).
[22] Cho, D. C.; Kim, W. Y., "Long-range gaze tracking system for large movements", IEEE Transactions on Biomedical Engineering, vol. 60, no. 12, pp. 3432-3440 (2013).
[23] Baek, S. J.; Choi, K. A.; Ma, C.; Kim, Y. H.; Ko, S. J., "Eyeball model-based iris center localization for visible image-based eye-gaze tracking systems", IEEE Transactions on Consumer Electronics, vol. 59, no. 2, pp. 415-421 (2013).
[24] Timm, F.; Barth, E., "Accurate Eye Centre Localization by Means of Gradients" Visapp, vol. 11, pp. 125-130 (2011).
[25] Campadelli, P.; Lanzarotti, R.; Lipori, G., "Precise Eye Localization through a General-to-specific Model Definition", In BMVC vol. 1, pp. 187-196 (2006).
[26] Dorigo, M.; Birattari, M., "Ant colony optimization", In Encyclopedia of machine learning, pp. 36-39 (2011).
[27] Prakasam, A.; Savarimuthu, N., "Metaheuristic algorithms and probabilistic behaviour: a comprehensive analysis of Ant Colony Optimization and its variants", Artificial Intelligence Review, vol. 45, no. 1, pp. 97-130 (2016).
[28] Hao, Z.; Zhang, X.; Yu, P.; Li, H., "Video object tracing based on particle filter with ant colony optimization", In Advanced Computer Control (ICACC), 2010 2nd International Conference on vol. 3, pp. 232-236. IEEE (2010).
[29] Kim, H. I.; Kim, J. B.; Park, R. H., "Efficient and Fast Iris Localization Using Binary Radial Gradient Features for Human–Computer Interaction", International Journal of Pattern Recognition and Artificial Intelligence, vol. 31, no. 11, (2017).
[30] Chen, B.; Chen, L.; Chen, Y., "Efficient ant colony optimization for image feature selection", Signal processing, vol. 93, no. 6, pp. 1566-1576 (2013).
[31] Valenti, R.; Gevers, T., "Accurate eye center location through invariant isocentric patterns", IEEE transactions on pattern analysis and machine intelligence, vol. 34, no. 9, pp.1785-1798 (2012).
[32] Srivastava, D. K.; Budhraja, T., "An Effective Model for Face Detection Using R, G, B Color Segmentation with Genetic Algorithm", In Proceedings of First International Conference on Information and Communication Technology for Intelligent Systems, vol. 2, pp. 47-55 (2016).
[33] Kumar, P.; Shashidhara, M., "Skin color segmentation for detecting human face region in image", In Communications and Signal Processing (ICCSP), 2014 International Conference on pp. 001-005. IEEE (2014).
[34] Rivera, A. R.; Castillo, J. R.; Chae, O. O., "Local directional number pattern for face analysis: Face and expression recognition", IEEE transactions on image processing, vol. 22, no. 5, pp. 1740-1752 (2013).
[35] Zhang, T.; Tang, Y. Y.; Fang, B.; Shang, Z.; Liu, X., "Face recognition under varying illumination using gradientfaces", IEEE Transactions on Image Processing, vol. 18, no. 11, pp. 2599-2606 (2009).
[36] Kirsch, R. A., "Computer determination of the constituent structure of biological images", Computers and biomedical research, vol. 4, no. 3, pp. 315-328 (1971).
[37] Cortes, C.; Vapnik, V., "Support-vector networks", Machine learning, vol. 20, no. 3, pp. 273-297 (1995).
[38] Florea, L.; Florea, C.; Vrânceanu, R.; Vertan, C., "Can Your Eyes Tell Me How You Think? A Gaze Directed Estimation of the Mental Activity", In BMVC (2013).
[39] Valenti, R.; Sebe, N.; Gevers, T., "Combining head pose and eye location information for gaze estimation", IEEE Transactions on Image Processing, vol. 21, no. 2, pp. 802-815 (2012).
[40] Goldberg, D. E., "Genetic Algorithms in Search, Optimization, and Machine Language", Addison-Wesley: Reading, UK (1989).
[41] Luengo-Oroz, M. A.; Faure, E.; Angulo, J., "Robust iris segmentation on uncalibrated noisy images using mathematical morphology", Image and Vision Computing, vol. 28, no. 2, pp. 278-284 (2010).
[42] Haralick, R. M.; Sternberg, S. R.; Zhuang, X., "Image analysis using mathematical morphology", IEEE transactions on pattern analysis and machine intelligence, vol. 4, pp. 532-550 (1987).
