Year: 2026
Type: article
Abstract: 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. Eye tracking relies on ocular features, that are susceptible to interference from light and individual variations. Here, Zhu et. al. present eye movement feature enhanced cosmetic contact lenses, enabling accurate, natural, and homogenized eye tracking.
Source: Nature Communications
Authors: Hengtian Zhu, Heyu Huang, Huan Yang, Zixu Li, Zhenning Qi, Yuan Fang, Yining Xu, Yifeng Xiong, Ye Chen, Songtao Yuan, Fei Xu
Language: English
Subfield: Human-Computer Interaction
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $6,990
Funders: National Natural Science Foundation of China, China Postdoctoral Science Foundation, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province, National Science and Technology Major Project, Basic Research Program of Jiangsu Province, National Key Research and Development Program of China
OpenAlex ID: W7127327160
