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相关概念视频

Relative Motion Analysis using Rotating Axes01:25

Relative Motion Analysis using Rotating Axes

433
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...
433
Absolute Motion Analysis- General Plane Motion01:24

Absolute Motion Analysis- General Plane Motion

193
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...
193
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

369
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...
369
Relative Motion Analysis - Velocity01:24

Relative Motion Analysis - Velocity

327
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...
327
Relative Motion Analysis using Rotating Axes - Acceleration01:22

Relative Motion Analysis using Rotating Axes - Acceleration

309
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...
309
Relative Motion Analysis - Acceleration01:10

Relative Motion Analysis - Acceleration

313
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...
313

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相关实验视频

Updated: May 9, 2025

A View of Their Own: Capturing the Egocentric View of Infants and Toddlers with Head-Mounted Cameras
03:56

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Published on: October 5, 2018

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来自小型摄像机运动视频的动态视图合成.

Huiqiang Sun, Xingyi Li, Juewen Peng

    IEEE transactions on visualization and computer graphics
    |April 29, 2025
    PubMed
    概括

    本研究引入了基于分布的深度调节 (DDR),以改进动态3D场景的新视图合成,以限制摄像机运动. DDR增强了场景几何表示和摄像机参数估计,以获得更好的染精度.

    科学领域:

    • 计算机视觉 计算机视觉
    • 3D 图形 3D 图形
    • 机器学习 机器学习

    背景情况:

    • 对动态3D场景的新视图合成具有挑战性,特别是在相机运动有限的情况下.
    • 当前基于NeRF的方法在运动抛物线不足时,与不准确的几何和相机参数作斗争.

    研究的目的:

    • 开发一种可靠的方法,用于用小型摄像机运动合成动态3D场景的新视图合成.
    • 解决场景几何表示和摄像机参数估计方面的挑战.

    主要方法:

    • 建议基于分布的深度调整 (DDR),以使染重量分布与真实分布保持一致.
    • 使用Gumbel-softmax进行可差分采样,并计算出预期的误差.
    • 引入了对体积密度的限制,以确保正确的场景几何学习.
    • 在训练期间内置相机参数学习,以提高强度.

    主要成果:

    • 在用有限的摄像机运动输入来表现场景方面表现出有效性.
    • 与最先进的方法进行了有利的比较.
    • 提出了一个可视化工具,用于解开DDR和观察场景几何.

    结论:

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    • 拟议的DDR方法显著改善了动态3D场景的新视图合成,相机运动有限.
    • 这种方法提高了几何精度和相机参数估计的稳定性.
    • 该方法为具有挑战性的视图合成场景提供了一个有希望的解决方案.