Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Beyond Barriers: Active Packaging Strategies for Sustainable Food Protection.

Polymers·2026
Same author

Nonclinical Safety Assessment of Digadoglucitol, a Novel Magnetic Resonance Imaging Contrast Agent for the Central Nervous System.

Investigative radiology·2026
Same author

Artificial Intelligence in Spine Imaging Interpretation.

Seminars in musculoskeletal radiology·2026
Same author

Artificial Intelligence in hepatology: A position paper by the Italian Association for the Study of the Liver.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver·2026
Same author

Zein-based polysaccharide-tannic acid films as multifunctional barriers to prevent post-surgical adhesions.

International journal of pharmaceutics: X·2026
Same author

Toward personalized persuasive social robots for behavior change in healthcare: a conceptual framework.

Frontiers in robotics and AI·2026

相关实验视频

Updated: Apr 27, 2026

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

9.2K

动态点云的视觉突出性比较:无任务与依赖任务的比较.

Xuemei Zhou, Irene Viola, Silvia Rossi

    IEEE transactions on visualization and computer graphics
    |March 11, 2025
    PubMed
    概括

    一个新的Task-Free眼睛跟踪数据集 (TF-DPC) 揭示了任务如何影响虚拟现实中的动态点云中的视觉注意力. 特定任务的目标显著改变了人们看的方向,影响了视觉突出模型.

    科学领域:

    • 计算机视觉 计算机视觉
    • 人与计算机的交互
    • 虚拟现实 虚拟现实 虚拟现实

    背景情况:

    • 了解人类视觉注意力对于有效的人机交互至关重要.
    • 虚拟现实中的动态点云为视觉注意力研究带来了独特的挑战.
    • 现有的数据集往往缺乏无任务条件,限制了对任务依赖注意力的研究.

    研究的目的:

    • 介绍动态点云 (TF-DPC) 的无任务眼睛跟踪数据集.
    • 在VR中调查高级任务对人类视觉注意力的影响.
    • 从无任务和任务依赖的实验中比较视觉突出性地图.

    主要方法:

    • 收集了24名参与者在VR环境中的眼睛凝视和头部运动数据.
    • 参与者观察了19个扫描的动态点云,自由度为6度.
    • 利用皮尔森相关性和适应的地球移动器距离来比较突出地图.

    主要成果:

    • 定性和定量分析显示,基于任务影响,视觉注意力存在显著差异.
    • 视觉突出性地图主要在无任务和任务依赖条件之间存在显著差异.
    • 视线和运动轨迹为动态点云,特别是人形的注意力提供了洞察力.

    更多相关视频

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    1.3K
    Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
    07:12

    Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

    Published on: April 11, 2025

    1.0K

    相关实验视频

    Last Updated: Apr 27, 2026

    Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
    13:00

    Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

    Published on: January 23, 2017

    9.2K
    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications
    03:31

    Author Spotlight: Enhancement of Salient Object Detection for Smart Grid Applications

    Published on: December 15, 2023

    1.3K
    Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss
    07:12

    Development of a Gaze-Contingent Display Framework Designed for Perceptual and Oculomotor Research with Simulated Central Vision Loss

    Published on: April 11, 2025

    1.0K

    结论:

    • 高级任务在VR中的动态点云观测中显著影响视觉注意力.
    • TF-DPC数据集为研究任务依赖的视觉注意力提供了有价值的数据.
    • 结果指导了改进的视觉突出模型和VR感知系统的开发.