Abstract
This paper proposes an unobtrusive and calibration-free framework towards eye gaze tracking based interactive directional control interface for desktop environment using simple webcam under unconstrained settings. The proposed eye gaze tracking involved hybrid approach designed by combining two different techniques based upon both supervised and unsupervised methods wherein the unsupervised image gradients method computes the iris centers over the eye regions extracted by the supervised regression based algorithm. Experiments performed by the proposed hybrid approach to detect eye regions along with iris centers over challenging face image datasets exhibited exciting results. Similar approach for eye gaze tracking worked well in real-time by using a simple web camera. Further, PC based interactive directional control interface based upon iris position has been designed that works without needing any prior calibrations unlike other Infrared illumination based eye trackers.
The proposed work may be useful to the people with full body motor disabilities, who need interactive and unobtrusive eye gaze control based applications to live independently.
Similar content being viewed by others
References
Burgos-Artizzu XP, Perona P, Dollar P (2013) Robust Face Landmark Estimation under Occlusion. Proceedings of the 2013 IEEE International Conference on Computer Vision, IEEE Computer Society: 1513–1520
Chang X, Yang Y (2017) Semisupervised feature analysis by mining correlations among multiple tasks. IEEE Trans Neural Netw Learn Syst 28(10):2294–2305
Chang X et al (2016) Compound rank-<inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula>projections for bilinear analysis. IEEE Trans Neural Netw Learn Syst 27(7):1502–1513
Database, B.F., BioID Face Database. https://www.bioid.com/About/BioID-Face-Database
Database, T.M.F., The MUCT Face Database , http://www.milbo.org/muct/
Feit A et al. (2017) Toward Everyday Gaze Input: Accuracy and Precision of Eye Tracking and Implications for Design: 1118–1130
Han Z et al (2014) Precise localization of eye centers with multiple cues. Multimed Tools Appl 68(3):931–945
Hansen DW, Qiang J (2010) In the eye of the beholder: a survey of models for eyes and gaze. Pattern Anal Mach Intell IEEE Trans 32(3):478–500
Jesorsky O, Kirchberg K, Frischholz R (2001) Robust face detection using the hausdorff distance. In: Bigun J, Smeraldi F (eds) Audio- and video-based biometric person authentication. Springer, Berlin Heidelberg, pp 90–95
Labeled Faces in the Wild
Laddi A, Prakash NR (2015) Comparative analysis of unsupervised eye center localization approaches. Signal Processing, Computing and Control (ISPCC), 2015 International Conf. IEEE
Laddi A, Prakash NR (2017) An augmented image gradients based supervised regression technique for iris center localization. Multimed Tools Appl 76(5):7129–7139
Laddi A, Prakash NR (2017) An accurate and simple approach to detect eye centers in low resolution face images. IETE J Res: 1–6
Leo M et al (2013) Unsupervised approach for the accurate localization of the pupils in near-frontal facial images. J Electron Imag 22(3):033033–033033
Leo M et al (2014) Unsupervised eye pupil localization through differential geometry and local self-similarity matching. PLoS One 9(8):e102829
Li B, Fu H (2018) Real time eye detector with cascaded convolutional neural networks. Appl Comput Intell Soft Comput 2018:8
Li Z et al (2017) Beyond trace ratio: weighted harmonic mean of trace ratios for multiclass discriminant analysis. IEEE Trans Knowl Data Eng 29(10):2100–2110
Liu L et al. (2018) From BoW to CNN: two decades of texture representation for texture classification. Int J Comput Vis
Lowe DG (2004) Distinctive image features from scale-invariant Keypoints. Int J Comput Vis 60(2):91–110
Matthews I, Baker S (2004) Active appearance models revisited. Int J Comput Vis 60(2):135–164
San Agustin, J., et al., (2010) Evaluation of a low-cost open-source gaze tracker. 77–80
Sewell W, Komogortsev O (2010) Real-time eye gaze tracking with an unmodified commodity webcam employing a neural network, in CHI '10 Extended Abstracts on Human Factors in Computing Systems. ACM: Atlanta, Georgia, USA: 3739-3744
Shaoqing R et al. (2014) Face alignment at 3000 FPS via Regressing Local Binary Features. in Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conf
TalkingFacevideo, Talking Face Video Database, http://www-prima.inrialpes.fr/FGnet/data/01-TalkingFace/talking_face.html
Timm F, Barth E (2011) Accurate eye centre localisation by means of gradients. Proceedings of the International Conference on Computer Vision Theory and Applications
Valenti R, Gevers T (2008) Accurate eye center location and tracking using isophote curvature. Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference
Viola P, Jones M (2001) Rapid object detection using a boosted cascade of simple features. in Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference
Xu P et al. (2015) TurkerGaze: Crowdsourcing saliency with webcam based eye tracking. CoRR. abs/1504.06755
Xudong C et al. (2012) Face alignment by Explicit Shape Regression. Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference
Xuehan X, de la Torre F (2013) Supervised descent method and its applications to face alignment. Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference
Ye L et al. (2014) Cascaded Convolutional Neural Network for Eye Detection Under Complex Scenarios. In Biometric Recognition. Cham: Springer International Publishing
Yuan-Pin L et al. (2005) Webcam Mouse Using Face and Eye Tracking in Various Illumination Environments. 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference
Zafeiriou S, Zhang C, Zhang Z (2015) A survey on face detection in the wild. Comput Vis Image Underst 138(C):1–24
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Laddi, A., Prakash, N.R. Eye gaze tracking based directional control interface for interactive applications. Multimed Tools Appl 78, 31215–31230 (2019). https://doi.org/10.1007/s11042-019-07940-3
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-019-07940-3