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

Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

Visualize a drone, with its propellers spinning rapidly, hovering mid-air. The fascinating movements and operations of this drone can be comprehended by applying the principle of general plane motion.
As the drone's propellers rotate, an upward force is generated that counteracts the force of gravity, enabling the drone to lift off from the ground. This initial movement of the drone is along a straight path, representing a form of translational motion. In this phase, every point on the drone...
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

A slider-crank mechanism converts rotational motion from the crank into linear motion of the slider or vice versa. This mechanism consists of three main parts: the crank, the connecting rod, and the slider. The movement of the slider-crank is an example of general plane motion as the fluctuating angle between the crank and the connecting rod. Consider a segment AB where point A is at the end of the slider and point B is on the diametrically opposite end to point A, on a crack. The variance in...

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

Patterns of Muscle Health in Single- and Multi-Site Chronic Pain: A UK Biobank Normative Modeling Study.

medRxiv : the preprint server for health sciences·2026
Same author

Neural Shape Modeling Reveals Early and Progressive Femoral Bone Shape and Cartilage Thickness Changes After Anterior Cruciate Ligament Reconstruction.

medRxiv : the preprint server for health sciences·2026
Same author

The menstrual cycle through the lens of a wearable device: insights into physiology, sleep, and cycle variability.

NPJ digital medicine·2026
Same author

Integrating Machine Learning with Musculoskeletal Simulation Improves OpenCap Video-Based Dynamics Estimation.

IEEE transactions on bio-medical engineering·2026
Same author

BMI and Varus Malalignment Compound to Define a High-Risk Phenotype for Compartment-Specific Knee Osteoarthritis Progression.

medRxiv : the preprint server for health sciences·2026
Same author

Smartphone video-based knee extension moments during chair rise relate to MRI measures of muscle function.

medRxiv : the preprint server for health sciences·2026

相关实验视频

Updated: Jun 9, 2026

Movement Retraining using Real-time Feedback of Performance
08:16

Movement Retraining using Real-time Feedback of Performance

Published on: January 17, 2013

13.4K

标记数据增强用于无标记的动作捕捉.

Antoine Falisse1, Scott D Uhlrich1, Akshay S Chaudhari2

  • 1Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.

bioRxiv : the preprint server for biology
|July 29, 2024
PubMed
概括
此摘要是机器生成的。

我们开发了一种改进的标记增强器,用于人类姿势估计,显著提高动力学准确性和对各种运动的概括性. 这一进步为使用OpenCap服务的研究人员提供了更精确的运动分析.

关键词:
深度学习是一种深度学习.没有标记的移动捕捉.肌肉骨的建模和模拟.构成估计估计的估计.轨道优化轨道优化

更多相关视频

3D Kinematic Gait Analysis for Preclinical Studies in Rodents
10:19

3D Kinematic Gait Analysis for Preclinical Studies in Rodents

Published on: August 3, 2019

10.7K
Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents
04:37

Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents

Published on: July 6, 2022

2.4K

相关实验视频

Last Updated: Jun 9, 2026

Movement Retraining using Real-time Feedback of Performance
08:16

Movement Retraining using Real-time Feedback of Performance

Published on: January 17, 2013

13.4K
3D Kinematic Gait Analysis for Preclinical Studies in Rodents
10:19

3D Kinematic Gait Analysis for Preclinical Studies in Rodents

Published on: August 3, 2019

10.7K
Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents
04:37

Comprehensive Understanding of Inactivity-Induced Gait Alteration in Rodents

Published on: July 6, 2022

2.4K

科学领域:

  • 生物力学 生物力学
  • 计算机视觉 计算机视觉
  • 机器学习 机器学习

背景情况:

  • 从视频中估计人类姿势,提供可扩展,低成本的运动分析.
  • 现有的开源模型往往产生不准确的关节动力学由于稀疏的关键点检测.
  • OpenCap的标记增强器提高了关键点密度,但与未代表的移动作斗争.

研究的目的:

  • 开发一种更准确,更可通用的标记增强剂,用于人类姿势估计.
  • 为了提高OpenCap服务的动力测量能力.
  • 扩大通过姿势估计模型准确分析的运动范围.

主要方法:

  • 编译了来自1176名受试者的基于标记器的运动捕捉数据.
  • 合成了1433小时的关键点和解剖学标记,用于训练.
  • 在基准和新型移动数据集上评估增强器的准确性.

主要成果:

  • 新的标记增强器在基准运动中实现了4.1°的平均动力学误差,超过了以前的方法.
  • 与OpenCap的原始增强器 (40.4°) 相比,对未见的运动具有更高的概括性,平均误差为4.1°.
  • 显著减少了各种运动的最大动力误差,从252.0°降至6.7°.

结论:

  • 增强的标记增强器在各种人类运动中提供了高精度和广泛的概括性.
  • 集成到OpenCap可以为成千上万的用户提供更可靠的运动测量.
  • 这项工作推进了基于视频的姿势估计对生物力学研究的有用性.