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眼睛追踪的全面框架:方法,工具,应用程序和跨平台评估

Govind Ram Chhimpa1, Ajay Kumar2, Sunita Garhwal2

  • 1Department of Internet of Things and Intelligent Systems, Manipal University Jaipur, Jaipur 303007, Rajasthan, India.

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概括
此摘要是机器生成的。

这项研究探讨了现代的眼睛跟踪技术,包括视频眼镜和深度学习,以加强视线分析. 它强调了它们在HCI,医疗保健和VR中的应用,并讨论了眼睛跟踪技术的未来方向.

关键词:
电脑脑电图 (EEG) 是一种电脑电图.电脑眼镜摄影 (electrooculography) 是一种电脑眼镜的使用方法.眼睛跟踪 眼睛跟踪眼睛追踪性能参数的性能参数眼睛追踪工具 眼睛追踪工具人与计算机的互动.脊椎卷圈是指脊椎的卷圈,是指脊椎卷圈.视频眼镜学视频眼镜学

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科学领域:

  • 计算机科学 计算机科学
  • 人与计算机的交互
  • 生物医学工程 生物医学工程

背景情况:

  • 眼睛跟踪对于凝视分析至关重要,用于HCI,教育,医疗保健和虚拟现实中的应用,测量眼睛运动.
  • 现代的眼睛跟踪在过去二十年中发生了显著的进化,结合了先进的技术.

研究的目的:

  • 提供眼睛跟踪概念,术语,性能参数和技术的全面概述.
  • 专注于当代和高效的眼睛跟踪方法,包括基于VOG的系统,用于目光估计的深度学习和可穿戴设备.
  • 探索眼睛跟踪与VR/AR和辅助技术的整合.

主要方法:

  • 对现代眼睛跟踪技术的审查,包括视频眼镜 (VOG) 和深度学习模型用于目光估计.
  • 分析可穿戴和具有成本效益的眼睛追踪设备.
  • 检查与虚拟/增强现实和辅助技术的整合策略.
  • 利用机器学习进行数据洞察和减少手动校准.

主要成果:

  • 当代的眼睛追踪方法显著提升了应用程序的开发.
  • 机器学习增强了决策,并最大限度地减少了眼睛跟踪中的校准需求.
  • 多种不同的眼睛跟踪技术对于推进各种应用至关重要.

结论:

  • 眼睛追踪是一个重要的工具,具有多样化的应用,现代技术显著增强了它.
  • 解决眼睛追踪方法的局限性和挑战是进一步发展的关键.
  • 未来的方向表明,通过先进的眼睛跟踪,用户体验的持续发展和丰富.