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Mouse calibration aided real-time gaze estimation based on boost Gaussian Bayesian learning | IEEE Conference Publication | IEEE Xplore

Mouse calibration aided real-time gaze estimation based on boost Gaussian Bayesian learning


Abstract:

In this paper, we propose a novel gaze estimation method to evaluate the attention span of users upon on-screen content via a single webcam. Our method is based on superv...Show More

Abstract:

In this paper, we propose a novel gaze estimation method to evaluate the attention span of users upon on-screen content via a single webcam. Our method is based on supervised descent method for eye region of interest (ROI) extraction. Then, boost Gaussian Bayesian regressors are applied to learn a robust mapping from the input eye ROI to gaze coordinates. To get enough training samples, we implant our scheme as a plug-in into web browsers for data collection from users without bothering. To improve accuracy, we also introduce mouse click to help train the regressors. Experiment results show that our method outperforms the existing method and can provide gaze estimation data for user behaviour analysis in real-time implementation.
Date of Conference: 25-28 September 2016
Date Added to IEEE Xplore: 08 December 2016
ISBN Information:
Electronic ISSN: 2381-8549
Conference Location: Phoenix, AZ, USA

References

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