Robust Gaze Estimation via Normalized Iris Center-Eye Corner Vector
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Gaze estimation plays an important role in many practical scenarios such as human robot interaction. Although high accurate gaze estimation could be obtained in constrained settings with additional IR sources or depth sensors, single web-cam based gaze estimation still remains challenging. This paper propose a normalized iris center-eye corner (NIC-EC) vector based gaze estimation methods using a single, low cost web-cam. Firstly, reliable facial features and pupil centers are extracted. Then, the NIC-EC vector is proposed to enhance the robustness and accuracy for pupil center-eye corner vector based gaze estimations. Finally, an interpolation method is employed for the mapping between constructed vectors and points of regard. Experimental results showed that the proposed method has significantly improved the accuracy over the pupil center-eye corner vector based gaze estimation method with average accuracy of \(1.66^\circ \) under slight head movements.
KeywordsGaze estimation Eye tracking Normalized iris center-eye corner vector Interpolation
This work was supported by EU Seventh Framework Programme (611391, Development of Robot-Enhanced therapy for children with AutisM spectrum disorders (DREAM)) and National Natural Science Foundation of China (61403342,U1509207,61325019,61273286) and China Scholarship Council (201408330184).
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