<p>Vision-based analysis of ocular features represents the predominant approach for eye tracking. However, these features are highly susceptible to interference from illumination, eyelid/eyelash occlusion, and individual variations, leading to low recognition rates and diminished tracking accuracy. To address these limitations, eye movement feature enhanced cosmetic contact lenses are proposed, implementing a spatial-chromatic encoding strategy. Employing a head-mounted eye tracker integrated with RGB cameras, this system enables accurate and robust gaze tracking in natural environments. Under challenging illumination, the lenses achieve a 93% feature recognition rate, significantly surpassing pupil recognition and tolerating highly off-axis camera placement. Eye movement model and human eye tracking demonstrate superior accuracy (&lt;1°), gaze direction estimation, and continuous fixation positioning. Utilizing these lenses, diverse eye-tracking applications are demonstrated, including image identification, reading analysis, and outdoor interaction. This approach advances the development of lightweight, unobtrusive eye-tracking systems and facilitates broader application of gaze-based interaction technology in real-world settings.</p>

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Spatial-chromatic encoding cosmetic contact lenses for enhanced natural eye tracking

  • Hengtian Zhu,
  • Heyu Huang,
  • Huan Yang,
  • Zixu Li,
  • Zhenning Qi,
  • Yuan Fang,
  • Yining Xu,
  • Yifeng Xiong,
  • Ye Chen,
  • Songtao Yuan,
  • Fei Xu

摘要

Vision-based analysis of ocular features represents the predominant approach for eye tracking. However, these features are highly susceptible to interference from illumination, eyelid/eyelash occlusion, and individual variations, leading to low recognition rates and diminished tracking accuracy. To address these limitations, eye movement feature enhanced cosmetic contact lenses are proposed, implementing a spatial-chromatic encoding strategy. Employing a head-mounted eye tracker integrated with RGB cameras, this system enables accurate and robust gaze tracking in natural environments. Under challenging illumination, the lenses achieve a 93% feature recognition rate, significantly surpassing pupil recognition and tolerating highly off-axis camera placement. Eye movement model and human eye tracking demonstrate superior accuracy (<1°), gaze direction estimation, and continuous fixation positioning. Utilizing these lenses, diverse eye-tracking applications are demonstrated, including image identification, reading analysis, and outdoor interaction. This approach advances the development of lightweight, unobtrusive eye-tracking systems and facilitates broader application of gaze-based interaction technology in real-world settings.