Padikal Varun, Plonkowski Alex, Lawton Penelope F, Young Laura K, Read Jenny C A
Department of Biosciences, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
School of Medicine, Newcastle University, Newcastle upon Tyne NE1 7RU, UK.
Vision (Basel). 2025 Apr 3;9(2):29. doi: 10.3390/vision9020029.
Eye tracking technology plays a crucial role in various fields such as psychology, medical training, marketing, and human-computer interaction. However, achieving high accuracy over a larger field of view in eye tracking systems remains a significant challenge, both in free viewing and in a head-stabilized condition. In this paper, we propose a simple approach to improve the accuracy of video-based eye trackers through the implementation of linear coordinate transformations. This method involves applying stretching, shearing, translation, or their combinations to correct gaze accuracy errors. Our investigation shows that re-calibrating the eye tracker via linear transformations significantly improves the accuracy of video-based tracker over a large field of view.
眼动追踪技术在心理学、医学培训、市场营销和人机交互等各个领域都发挥着至关重要的作用。然而，在眼动追踪系统中，要在更大的视野范围内实现高精度，无论是在自由观看还是头部稳定的情况下，仍然是一项重大挑战。在本文中，我们提出了一种简单的方法，通过实施线性坐标变换来提高基于视频的眼动追踪器的准确性。该方法包括应用拉伸、剪切、平移或它们的组合来校正注视准确性误差。我们的研究表明，通过线性变换重新校准眼动追踪器可显著提高基于视频的追踪器在大视野范围内的准确性。
