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

Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

393
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
393
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

382
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...
382
Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

441
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.
However, to express the relative position of point B relative to point A, an additional frame of reference, denoted as x'y', is necessary. This additional frame not only translates but also rotates relative to the fixed frame, making it...
441
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

199
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...
199
Kinematic Equations: Problem Solving01:15

Kinematic Equations: Problem Solving

11.8K
When analyzing one-dimensional motion with constant acceleration, the problem-solving strategy involves identifying the known quantities and choosing the appropriate kinematic equations to solve for the unknowns. Either one or two kinematic equations are needed to solve for the unknowns, depending on the known and unknown quantities. Generally, the number of equations required is the same as the number of unknown quantities in the given example. Two-body pursuit problems always require two...
11.8K
Curvilinear Motion: Normal and Tangential Components01:27

Curvilinear Motion: Normal and Tangential Components

371
When a car traverses a curved road, its motion can be elucidated by breaking it down into tangential and normal components. The car-centric coordinates attached to the vehicle move with it.
The positive direction of the t-axis aligns with the increasing position of the car along the curved path, denoted by the unit vector ut. Simultaneously, the n-axis, perpendicular to the t-axis, dissects the curved path into differential arc segments, each forming the arc of a circle with a radius of...
371

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

A unified multi-modal foundation model for end-to-end emergency care.

NPJ digital medicine·2026
Same author

Long-Term Trends in the Burden of Bipolar Disorder in China, 1990-2052: An Analysis of the Global Burden of Disease Study 2023.

Psychology research and behavior management·2026
Same author

A risk-based post ablation follow-up strategy for hepatocellular carcinoma.

JHEP reports : innovation in hepatology·2026
Same author

Decoupled Seg Tokens Make Stronger Reasoning Video Segmenter and Grounder.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

MMA++: Effective Multi-Modal Adaptation for Vision-Language Models.

IEEE transactions on pattern analysis and machine intelligence·2026
Same author

EcoRxAgent: an AI agent for generating economically substitutable prescriptions.

NPJ digital medicine·2026

相关实验视频

Updated: May 24, 2025

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.5K

基于线性轨迹的跨摄像头行人轨迹检索方式

Xin Zhang, Xiaohua Xie, Jianhuang Lai

    IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
    |March 3, 2025
    PubMed
    概括

    本研究介绍了用于行人轨迹检索的时间旋转位置嵌入 (T-RoPE),通过仅使用时间数据来简化模型. 这种方法提高了在多个摄像头上跟踪个人的准确性,而无需复杂的空间要求.

    科学领域:

    • 计算机视觉 计算机视觉
    • 人工智能的人工智能
    • 机器学习 机器学习

    背景情况:

    • 步行者轨迹检索对于分析人群流动和在摄像头网络中识别个人至关重要.
    • 传统方法需要大量的时空数据和摄像头位置信息,这给数据收集带来了重大挑战.
    • 现有的方法经常与多摄像头行人跟踪的复杂性作斗争.

    研究的目的:

    • 开发一种新的行人轨迹检索方法,绕过时空建模的需要.
    • 引入一个隐式轨迹编码方案,即时间旋转位置嵌入 (T-RoPE),以增强特征表示.
    • 提高多摄像头行人跟踪的效率和准确性.

    主要方法:

    • 提出了一个时间旋转位置嵌入 (T-RoPE) 方案,将时间信息直接编码为视觉表示.
    • 开发了一种方法,使用线性轨迹多元体在精致的特征空间内建模相机间轨迹提取.
    • 利用候选轨迹的视觉特征进行比较和对查询特征进行排名.

    主要成果:

    • T-RoPE模块有效地集成时间数据,为轨迹分析创造了一个新的功能空间.
    • 拟议的方法通过识别线性轨迹多元体,成功地解决了相机间轨迹提取挑战.
    • 实验表明,在各种数据集中,行人轨迹检索精度显著提高.

    更多相关视频

    Image-based Lagrangian Particle Tracking in Bed-load Experiments
    10:32

    Image-based Lagrangian Particle Tracking in Bed-load Experiments

    Published on: July 20, 2017

    8.9K
    Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography
    06:09

    Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

    Published on: March 12, 2021

    3.0K

    相关实验视频

    Last Updated: May 24, 2025

    Trajectory Data Analyses for Pedestrian Space-time Activity Study
    16:14

    Trajectory Data Analyses for Pedestrian Space-time Activity Study

    Published on: February 25, 2013

    13.5K
    Image-based Lagrangian Particle Tracking in Bed-load Experiments
    10:32

    Image-based Lagrangian Particle Tracking in Bed-load Experiments

    Published on: July 20, 2017

    8.9K
    Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography
    06:09

    Measuring 3D In-vivo Shoulder Kinematics using Biplanar Videoradiography

    Published on: March 12, 2021

    3.0K

    结论:

    • 时间旋转位置嵌入 (T-RoPE) 提供了一种多功能,插即用的解决方案,用于增强行人轨迹检索.
    • 该方法减少了对复杂时空数据的依赖,简化了检索过程.
    • 新推出的商场轨迹数据集和发布的代码有助于在该领域进行进一步的研究.