Regressor Based Estimation of the Eye Pupil Center

The locations of the eye pupil centers are used in a wide range of computer vision applications. Although there are successful commercial eye gaze tracking systems, their practical employment is limited due to required specialized hardware and extra restrictions on the users. On the other hand, the precision and robustness of the off the shelf camera based systems are not at desirable levels. We propose a general purpose eye pupil center estimation method without any specialized hardware. The system trains a regressor using HoG features with the distance between the ground-truth pupil center and the center of the train patches. We found HoG features to be very useful to capture the unique gradient angle information around the eye pupils. The system uses a sliding window approach to produce a score image that contains the regressor estimated distances to the pupil center. The best center positions of two pupils among the candidate centers are selected from the produced score images. We evaluate our method on the challenging BioID and Columbia CAVE data sets. The results of the experiments are overall very promising and the system exceeds the precision of the similar state of the art methods. The performance of the proposed system is especially favorable on extreme eye gaze angles and head poses. The results of all test images are publicly available.

[1]  Igor S. Pandzic,et al.  Eye pupil localization with an ensemble of randomized trees , 2014, Pattern Recognit..

[2]  Jiri Matas,et al.  Feature-based affine-invariant localization of faces , 2005, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[3]  Klaus J. Kirchberg,et al.  Robust Face Detection Using the Hausdorff Distance , 2001, AVBPA.

[4]  Paul A. Viola,et al.  Robust Real-Time Face Detection , 2001, International Journal of Computer Vision.

[5]  Qiang Ji,et al.  Multi-view face and eye detection using discriminant features , 2007, Comput. Vis. Image Underst..

[6]  Andrew W. Fitzgibbon,et al.  Real-time human pose recognition in parts from single depth images , 2011, CVPR 2011.

[7]  Naoki Mukawa,et al.  A free-head, simple calibration, gaze tracking system that enables gaze-based interaction , 2004, ETRA.

[8]  Steven K. Feiner,et al.  Gaze locking: passive eye contact detection for human-object interaction , 2013, UIST.

[9]  Dongheng Li,et al.  openEyes: a low-cost head-mounted eye-tracking solution , 2006, ETRA.

[10]  Antonio Albiol,et al.  Precise eye localization using HOG descriptors , 2011, Machine Vision and Applications.

[11]  Yusuf Sinan Akgül,et al.  Iterative estimation of the eye pupil center , 2015, 2015 23nd Signal Processing and Communications Applications Conference (SIU).

[12]  Linden J. Ball,et al.  Eye tracking in HCI and usability research. , 2006 .

[13]  Bill Triggs,et al.  Histograms of oriented gradients for human detection , 2005, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05).

[14]  Andrew T. Duchowski,et al.  Eye Tracking Methodology: Theory and Practice , 2003, Springer London.

[15]  Vincent Lepetit,et al.  Multiscale Centerline Detection by Learning a Scale-Space Distance Transform , 2014, 2014 IEEE Conference on Computer Vision and Pattern Recognition.

[16]  Theo Gevers,et al.  Accurate Eye Center Location through Invariant Isocentric Patterns , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Alexander J. Smola,et al.  Support Vector Regression Machines , 1996, NIPS.

[18]  G LoweDavid,et al.  Distinctive Image Features from Scale-Invariant Keypoints , 2004 .

[19]  Andrew J. Stewart,et al.  Integrating text and pictorial information: eye movements when looking at print advertisements. , 2001, Journal of experimental psychology. Applied.

[20]  Paola Campadelli,et al.  Precise Eye Localization through a General-to-specific Model Definition , 2006, BMVC.

[21]  Chengjun Liu,et al.  Precise Eye Detection Using Discriminating HOG Features , 2011, CAIP.

[22]  Erhardt Barth,et al.  Accurate Eye Centre Localisation by Means of Gradients , 2011, VISAPP.