JCSE, vol. 12, no. 2, pp.77-89, 2018

DOI: http://dx.doi.org/10.5626/JCSE.2018.12.2.77

Design and Analysis of Improved Iris-Based Gaze Estimation Model

Anjana Sharma and Pawanesh Abrol
Department of Computer Science, GGM Science College, Jammu, India Department of Computer Science & IT, University of Jammu, Jammu, India

Abstract: The detection accuracy of gaze direction mainly depends on the performance of features extracted from eye images. Limitations on the estimation of gaze direction include harmful infrared (IR) light, expensive devices, static thresholding, inappropriate and complex segmentation techniques, corneal reflections, etc. In this study, an efficient appearance cum feature-based detection model, namely, iris center-based gaze estimation (ICGE), has been proposed. The model is an extension of the earlier proposed glint-based gaze direction estimation (GDE) model and overcomes the above limitations. The ICGE model has been analyzed for GDE based on iris center coordinates using a local adaptive thresholding technique. An indigenous database using more than two hundred images of different subjects on a five quadrant map screen generates almost 90% accurate results for iris and gaze quadrant detection. The distinguishing features of the low cost, non-intrusive proposed model include a lack of IR and affordable ubiquitous H/W designing, large subject-camera distance and screen dimensions, no glint dependency, and many more. The proposed model also shows significantly better results in the lower periphery corners of the quadrant map than traditional models. In addition, aside from the comparison with the GDE model, the proposed model has also been compared with other existing techniques.

Keyword: Iris center based gaze estimation (ICGE) model; Adaptive thresholding; Iris center; Non-intrusive; Gaze quadrant detection; Glint

Full Paper:   467 Downloads, 1466 View