Abstract
Eye gaze-based system requires the correct estimation and detection of gaze. Gaze-based input is processed to initiate different commands remotely in computing systems. However, various factors like interactivity, processor affinity, distance, orientations, light, image resolution, etc., affect the detection of gaze in the eye gaze models. In this research paper, work has been done to evaluate the processing time for the estimation of gaze direction for detecting the variations in interactivity for gaze-based models w.r.t. distance and orientation parameters of the subject. The experimental work has been done using gaze detection and estimation (GDE) model. The different results obtained by varying the number of processor affinities for finding the minimum CPU time taken by the model for different eye images. These results can further be used for improving and minimizing the interactivity time for enhancing the accuracy and performance of eye gaze-based systems.
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References
Hansen, D. W. and Ji, Q.: In the Eye of the Beholder: A Survey of Models for Eyes and Gaze. vol. 32, 3, pp. 478–500, In: IEEE Computer Society (2010).
Sharma, A. and Abrol, P.: Eye Gaze Techniques for Human Computer Interaction: A Research Survey. Int. J. of Comput. Applicat. (IJCA), 71, pp. 18–29 (2013).
Sharma, A. and Abrol, P.: Comparative Analysis of Edge Detection Operators for Better Glint Detection. In: IEEE Proc. of IX INDIACOM, 2nd Int’l Conf. on Computing for Sustainable Global Development, pp. 973–977 (2015).
Gidlöf, K., Wallin, A., Dewhurst. R. and Holmqvist, K.: Using Eye Tracking to Trace a Cognitive Process: Gaze Behaviour During Decision Making in a Natural Environment. J. Eye Movement Research 6(1):3, 1–14 (2013).
Choo, C., Lee, J. W., Shin, K.Y., Lee, E. C. K., Park, R., Lee, H. and Cha. J.: Gaze Detection by Wearable Eye-Tracking and NIR LED-Based Head-Tracking Device Based on SVR. J. ETRI, vol. 34, 4, pp. 542–552 (2012).
Yang, C., Chae, J., Hung, C. and Kuo, T.: System-Level Energy-Efficiency for Real-Time Tasks. In: 10th IEEE Intl. Sym. On Object and Component-Oriented Real-Time Distributed Computing (2007).
Haibo. Z., Di Natale, M.: An Efficient Formulation of the Real-Time Feasibility Region for Design Optimization. In: IEEE Computer transactions, vol. 62 (4), pp. 644–661 (2012).
Sharma, D. and Abrol, P.: SVD Based Noise Removal Technique: An Experimental Analysis. Int. J. of Advanced Research in Computer Science, 3(5), pp. – 214–218 (2012).
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Anjana Sharma, Pawanesh Abrol (2016). Evaluating Interactivity with Respect to Distance and Orientation Variables of GDE Model. In: Satapathy, S., Bhatt, Y., Joshi, A., Mishra, D. (eds) Proceedings of the International Congress on Information and Communication Technology. Advances in Intelligent Systems and Computing, vol 438. Springer, Singapore. https://doi.org/10.1007/978-981-10-0767-5_20
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DOI: https://doi.org/10.1007/978-981-10-0767-5_20
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