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相关概念视频

Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

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Consider a crane whose telescopic boom rotates with an angular velocity of 0.04 rad/s and angular acceleration of 0.02 rad/s2. Along with the rotation, the boom also extends linearly with a uniform speed of 5 m/s. The extension of the boom is measured at point D, which is measured with respect to the fixed point C on the other end of the boom. For the given instant, the distance between points C and D is 60 meters.
Here, in order to determine the magnitude of velocity and acceleration for point...
389
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

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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...
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Anatomical Movements00:51

Anatomical Movements

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Anatomical movements refer to the various actions or motions that can be performed by the body's joints and muscles. These movements are described using specific terms to provide a standardized way of discussing and understanding the range of motion at different joints.
Here are some common anatomical movements:
Flexion and extension motions are in the sagittal (anterior–posterior) plane of motion. These movements take place at the shoulder, hip, elbow, knee, wrist,...
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Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

322
Consider a component AB undergoing a linear motion. Along with a linear motion, point B also rotates around point A. To comprehend this complex movement, position vectors for both points A and B are established using a stationary reference frame. The absolute velocity of point B is determined by adding the absolute velocity of point A, the relative velocity of point B in the rotating frame, and the effects caused by the angular velocity within the rotating frame.
Time differentiation is...
322
Muscle Coordination and Action01:24

Muscle Coordination and Action

1.3K
Muscle coordination is a complex and finely tuned process essential for smooth and purposeful movements like flexion, extension, adduction, abduction, and rotation. The human body orchestrates the actions of various muscles working in concert, each with a specific role. Four functional types describe how muscles work together: agonist, antagonist, synergist, and fixator.
Agonists
Agonist muscles, often called prime movers, are the primary muscles responsible for producing a specific movement....
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Relative Motion Analysis - Velocity01:24

Relative Motion Analysis - Velocity

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A stroke engine has a slider-crank mechanism that 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.
When an external force is exerted, it sets the crank into a rotational movement. This, in turn, instigates the motion of the connecting rod, leading to what is referred to as a general plane motion. This process involves two key points - point A on the connecting rod...
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相关实验视频

Updated: Jun 5, 2025

Estimation of Contact Regions Between Hands and Objects During Human Multi-Digit Grasping
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角度信息有助于基于骨架的行动识别.

Chengming Liu1, Jiahao Guan1, Haibo Pang1

  • 1School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou, Henan, China.

PeerJ. Computer science
|December 9, 2024
PubMed
概括
此摘要是机器生成的。

这项研究通过引入共弦流和关键采样来增强基于人类骨的动作识别,用于像花样滑冰这样的复杂活动. 这些方法在不改变核心网络的情况下提高了准确性,提高了对具有挑战性的数据集的性能.

关键词:
行动认可 行动认可角度信息 角度信息动画滑冰是人体滑冰的运动.骨架 骨架是一个骨.

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科学领域:

  • 计算机视觉 计算机视觉
  • 机器学习 机器学习
  • 人类行动识别 人类行动识别

背景情况:

  • 图形卷积网络 (GCNs) 在基于骨架的动作识别方面表现出色,但由于缺乏不变性和依赖可变运动数据,因此在复杂的动作方面陷入困境.
  • 现有的方法与视角扭曲和个体运动变异性作斗争,阻碍了像艺术滑冰识别等任务的性能.

研究的目的:

  • 为了提高基于骨架的行动识别对复杂的人类活动的稳定性和准确性.
  • 解决图形卷积网络 (GCNs) 在处理尺度,旋转和运动可变性的局限性.
  • 引入新的空间和时间特征提取方法,而不改变GCN骨干.

主要方法:

  • 开发了一种新的等号流,以增强空间特征的强度,防止扭曲.
  • 引入了一个Keyframe采样算法,用于高效和有效的时间特征提取,绕过运动信息.
  • 拟议的方法被整合,而不需要对现有的GCN骨干架构进行修改.

主要成果:

  • 与最先进的方法相比,在FSD-10艺术滑冰数据集上的Top-1准确度提高了2.6%.
  • 在FineGYM和NTU RGB+D数据集上表现出卓越的性能,验证了该方法的通用性.
  • 关键框架采样算法有效提取时间特征,减少对潜在误导性的运动数据的依赖.

结论:

  • 拟议的共弦值流和关键框架采样显著提高了基于骨架的复杂动作的动作识别.
  • 该方法提供了更高的准确性和稳定性,特别是在运动变化很高的活动中,如花样滑冰.
  • 这种方法为人类行动识别提供了宝贵的进步,在不进行建筑变更的情况下提供更好的性能.