Convolution-based means of gradient for fast eye center localization
Haibin Cai, Hui Ling Yu, Chunyan Yao, Shen-Yong Chen, Honghai Liu · 2015
Localizing eye center is primary challenge for application-s involving gaze estimation, face recognition and human machine interaction. The challenge is caused by significant variability of eye appearance in illumination, shape, color, viewing angle and dynamics, and computation related issues. In this paper, we propose a convolution-based means of gradient method to efficiently and accurately locate the eye center in low resolution images. Priority of enhancing its computation is achieved by the use of FFT transform and fewer identified pixels of circular boundary of potential eye centres. The proposed algorithm is validated in the research database platform of BioID face database. The experimental results confirm that the proposed outperforms the-state-of-art methods and its potential in real-time eye gaze tracking related applications.