A pupil location algorithm based on cascaded Haar feature and OTSU dynamic threshold segmentation

Fanxing Qian; Hao Lei

doi:10.1117/12.2607002

24 November 2021 A pupil location algorithm based on cascaded Haar feature and OTSU dynamic threshold segmentation

Fanxing Qian, Hao Lei

Proceedings Volume 12065, AOPC 2021: Optical Sensing and Imaging Technology; 120653I (2021) https://doi.org/10.1117/12.2607002
Event: Applied Optics and Photonics China 2021, 2021, Beijing, China

Abstract

With the development of visual human-computer interaction, non-invasive eye-tracking technology has been applied in medical diagnosis, psychological research, augmented reality and other fields. As a key step of video-based eye tracking technology, pupil detection requires strong robustness, real-time performance and high precision. Although many pupil detection algorithms have been developed, pupil detection is still a challenge when there are so many interference factors such as bright light, reflection, eyelid or eyelash occlusion, or low image resolution. Aim to address the above difficult problems of pupil detection, this paper uses cascaded Haar features and Otsu dynamic threshold segmentation to improve the performance of the existing pupil detection algorithm. The performance of the improved algorithm is verified with the public human eye image dataset from Swirski with high off-axis and severe eyelash occlusion. The results show that the accuracy of the improved algorithm is 86.3% and 89.7% in the error range of 5 pixels and 10 pixels, respectively. The detection algorithm in this paper can provide accurate pupil center coordinates for eye tracking, which lays a foundation for the high-precision calibration and measurement of the following eye tracker.

Citation Download Citation

Fanxing Qian and Hao Lei "A pupil location algorithm based on cascaded Haar feature and OTSU dynamic threshold segmentation", Proc. SPIE 12065, AOPC 2021: Optical Sensing and Imaging Technology, 120653I (24 November 2021); https://doi.org/10.1117/12.2607002

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