CondSeg: Ellipse Estimation of Pupil and Iris via Conditioned Segmentation
<|reference_start|>CondSeg: Ellipse Estimation of Pupil and Iris via Conditioned Segmentation: Parsing of eye components (i.e. pupil, iris and sclera) is fundamental for eye tracking and gaze estimation for AR/VR products. Mainstream approaches tackle this problem as a multi-class segmentation task, providing only visible part of pupil/iris, other methods regress elliptical parameters using human-annotated full pupil/iris parameters. In this paper, we consider two priors: projected full pupil/iris circle can be modelled with ellipses (ellipse prior), and the visibility of pupil/iris is controlled by openness of eye-region (condition prior), and design a novel method CondSeg to estimate elliptical parameters of pupil/iris directly from segmentation labels, without explicitly annotating full ellipses, and use eye-region mask to control the visibility of estimated pupil/iris ellipses. Conditioned segmentation loss is used to optimize the parameters by transforming parameterized ellipses into pixel-wise soft masks in a differentiable way. Our method is tested on public datasets (OpenEDS-2019/-2020) and shows competitive results on segmentation metrics, and provides accurate elliptical parameters for further applications of eye tracking simultaneously.<|reference_end|>
@article{jia2024condseg:,
    title={CondSeg: Ellipse Estimation of Pupil and Iris via Conditioned
  Segmentation},
    author={Zhuang Jia, Jiangfan Deng, Liying Chi, Xiang Long, Daniel K. Du},
    journal={arXiv preprint arXiv:2408.17231},
    year={2024},
    archivePrefix={arXiv},
    eprint={2408.17231},
    primaryClass={cs.CV}
}