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相关概念视频

Propagation of Uncertainty from Random Error00:59

Propagation of Uncertainty from Random Error

704
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
704
Propagation of Uncertainty from Systematic Error01:10

Propagation of Uncertainty from Systematic Error

534
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
534
Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

5.4K
It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
5.4K
Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

4.2K
In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
4.2K
Relative Motion Analysis using Rotating Axes-Problem Solving01:29

Relative Motion Analysis using Rotating Axes-Problem Solving

408
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...
408
Interference: Path Lengths01:10

Interference: Path Lengths

1.3K
Consider two sources of sound, that may or may not be in phase, emitting waves at a single frequency, and consider the frequencies to be the same.
Two special sources may be considered when they are in phase. This can be easily achieved by feeding the two sources from the same source. An example would be synchronizing the two speakers by feeding them with the same source, such as the sound waves produced by a tuning fork. This setup ensures that the two sources have the same frequency and are...
1.3K

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相关实验视频

Updated: Jul 13, 2025

Determining 3D Flow Fields via Multi-camera Light Field Imaging
14:25

Determining 3D Flow Fields via Multi-camera Light Field Imaging

Published on: March 6, 2013

16.7K

对于飞行时间传感器的多摄像头干扰的概率建模.

Bryan Rodriguez1, Xinxiang Zhang1, Dinesh Rajan1

  • 1Department of Electrical and Computer Engineering, Lyle School of Engineering, Southern Methodist University, Dallas, TX 75205, USA.

Sensors (Basel, Switzerland)
|October 14, 2023
PubMed
概括
此摘要是机器生成的。

在3D深度图中的多摄像头干扰会导致数据丢失. 本研究介绍了一个使用概率模型和光线追踪来准确预测和模拟这种干扰的框架,有助于制定缓解策略.

关键词:
三维图像处理是3D图像处理.深度地图,深度地图.多摄像头干扰的干扰飞行时间传感器

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Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
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Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

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Sample Drift Correction Following 4D Confocal Time-lapse Imaging
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Sample Drift Correction Following 4D Confocal Time-lapse Imaging

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相关实验视频

Last Updated: Jul 13, 2025

Determining 3D Flow Fields via Multi-camera Light Field Imaging
14:25

Determining 3D Flow Fields via Multi-camera Light Field Imaging

Published on: March 6, 2013

16.7K
Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
11:54

Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

Published on: March 13, 2017

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Sample Drift Correction Following 4D Confocal Time-lapse Imaging
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Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

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科学领域:

  • 计算机视觉 计算机视觉
  • 3D成像是3D成像中的一种.
  • 光学物理学的光学物理学

背景情况:

  • 红外 (IR) 3D成像中的多摄像头干扰尚未得到充分理解.
  • 干扰导致深度图中的零值像素增加,导致关键深度信息丢失.
  • 这种现象影响了3D成像系统的可靠性.

研究的目的:

  • 开发一个框架,以合成方式在3D图像中产生直接和间接的多摄像头干扰.
  • 创建一个数学模型,预测由干扰引起的零值像素的位置和概率.
  • 为了能够更好地理解和减轻3D深度传感中的多摄像头干扰.

主要方法:

  • 概率模型和光线跟踪的组合被用来产生合成干扰.
  • 开发了一个数学模型来预测干扰深度图中的零值像素分布.
  • 合成干扰图像与受控实验室捕获的图像进行了比较.

主要成果:

  • 该框架准确地预测了由于多摄像头干扰而丢失的深度信息的位置.
  • 对于直接干扰,该框架的平均RMSE为0.0625,PSNR为24.1277dB,SSIM为0.9007.
  • 对于间接干扰,该框架的平均RMSE为0.0312,PSNR为26.2280dB,SSIM为0.9064.

结论:

  • 拟议的框架有效地模拟了3D深度图中的多摄像头干扰.
  • 该模型在预测零值像素的准确性验证了它的实用性.
  • 这一框架对于开发和测试减轻干扰的技术至关重要,这对于推进3D成像技术至关重要.