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

Design Example: Measuring Distance Between Two Points with Obstructions01:10

Design Example: Measuring Distance Between Two Points with Obstructions

381
When measuring distances in areas with physical obstructions, such as a lake in a field, surveyors must employ techniques to calculate accurate lengths without direct line measurements. One effective method is the offset technique, which allows for precise distance estimation over inaccessible stretches.In this scenario, a surveyor must measure a side of an area that crosses a lake. Since the measuring tape cannot span the lake, the surveyor begins by establishing a baseline that aligns with...
381
Electronic Distance Measuring Instruments01:30

Electronic Distance Measuring Instruments

450
Electronic Distance Measuring Instruments (EDMs) are essential tools in modern surveying, offering precise distance measurements by emitting electromagnetic signals and calculating the time required for these signals to travel to a target and return. Two primary types of signals are used in EDMs — light waves and microwaves — each suited to specific environmental and distance requirements. Light-wave-based EDMs utilize either infrared or laser light, providing high accuracy over...
450
Distance Corrections01:15

Distance Corrections

262
To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
262
Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

7.2K
On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
7.2K
Distance Measurements by Taping01:18

Distance Measurements by Taping

397
Tapes are essential in surveying for accurate, durable, and short-distance measurements. Made from lightweight, nylon-coated steel, they offer flexibility and strength for rugged outdoor use. The nylon coating protects against rust and wear, extending the tape's life. Standard lengths, around 30 meters, are marked in meters and millimeters for precision.Surveyors select tapes based on site conditions and accuracy needs. Lightweight, nylon-coated tapes are commonly used for ease of handling and...
397
Common Leveling Mistakes and Errors01:17

Common Leveling Mistakes and Errors

385
A survey team is tasked with determining the elevation difference between points Point A and Point B, separated by uneven terrain. They use a leveling instrument and a leveling rod.Common MistakesMisreading the Rod: During a backsight reading at Point A, the instrumentman observes the rod partially obscured by tall grass. Instead of reading 1.135 m, they mistakenly record 1.735 m due to the misalignment of the crosshair with the wrong graduation. This error adds 0.600 m to all subsequent...
385

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 journal

RETRACTED: Ndaguba et al. Operability of Smart Spaces in Urban Environments: A Systematic Review on Enhancing Functionality and User Experience. <i>Sensors</i> 2023, <i>23</i>, 6938.

Sensors (Basel, Switzerland)·2026
Same journal

Correction: Ma et al. A Lightweight, Low-Frequency, Broadband Underwater Acoustic Transducer with Ternary Symmetric Excitation: Integrating KNN and Terfenol-D for Enhanced Performance. <i>2026</i>, <i>26</i>, 3645.

Sensors (Basel, Switzerland)·2026
Same journal

Correction: He et al. An Edge-Computing-Based Emotion-Aware Adaptive Lighting System for Intelligent Cockpits. <i>Sensors</i> 2026, <i>26</i>, 3489.

Sensors (Basel, Switzerland)·2026
Same journal

Correction: Tu et al. Lower Limb Motion Recognition with Improved SVM Based on Surface Electromyography. <i>Sensors</i> 2024, <i>24</i>, 3097.

Sensors (Basel, Switzerland)·2026
Same journal

Real-Time Detection System for Road Roughness Based on Ultrasonic Technology.

Sensors (Basel, Switzerland)·2026
Same journal

FedHSFV: Federated Learning for Finger Vein Recognition via Hierarchical Decoupling and Subspace Metric.

Sensors (Basel, Switzerland)·2026

相关实验视频

Updated: Jan 11, 2026

Novel Object Recognition and Object Location Behavioral Testing in Mice on a Budget
05:57

Novel Object Recognition and Object Location Behavioral Testing in Mice on a Budget

Published on: November 20, 2018

58.6K

室内物体通过冗余和比较方法进行测量.

Pedro Faria1, Tomás Simões2, Tiago Marques3

  • 1Infrastructure Department, Hainan University, Haikou 570228, China.

Sensors (Basel, Switzerland)
|November 13, 2025
PubMed
概括

这项研究提出了一个新的计算机视觉框架,用于使用标准智能手机摄像头进行准确的室内空间测量. 它克服了以前方法的局限性,通过利用几何和建筑规则来精确地估计墙壁和空间尺寸.

关键词:
空间LM 空间LM自动光学检查自动光学检查计算机视觉 计算机视觉深度学习是一种深度学习.几何学推断推断的结论室内空间建模室内空间建模工业质量检查 工业质量检查机器学习是机器学习.测量对象测量对象的测量房地产图像分析传感技术的感应技术.基于智能手机的传感器

更多相关视频

A Random-displacement Measurement by Combining a Magnetic Scale and Two Fiber Bragg Gratings
08:23

A Random-displacement Measurement by Combining a Magnetic Scale and Two Fiber Bragg Gratings

Published on: September 30, 2019

6.7K
Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
07:57

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision

Published on: April 29, 2014

13.9K

相关实验视频

Last Updated: Jan 11, 2026

Novel Object Recognition and Object Location Behavioral Testing in Mice on a Budget
05:57

Novel Object Recognition and Object Location Behavioral Testing in Mice on a Budget

Published on: November 20, 2018

58.6K
A Random-displacement Measurement by Combining a Magnetic Scale and Two Fiber Bragg Gratings
08:23

A Random-displacement Measurement by Combining a Magnetic Scale and Two Fiber Bragg Gratings

Published on: September 30, 2019

6.7K
Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision
07:57

Accuracy in Dental Medicine, A New Way to Measure Trueness and Precision

Published on: April 29, 2014

13.9K

科学领域:

  • 计算机视觉 计算机视觉
  • 几何深度学习 几何深度学习
  • 室内空间测量室内空间测量

背景情况:

  • 传统的计算机视觉方法在室内环境中难以准确地检测和测量物体,特别是在视觉参考有限的极简空间.
  • 现有的模型往往无法产生完整的检测或准确的距离估计,例如超过摄像机视野的墙壁等元素.

研究的目的:

  • 引入一种新的以几何驱动的,基于冗余的框架,以提高室内环境中的墙壁和空间划分的测量精度.
  • 为了使准确的空间测量只使用标准的智能手机摄像头,没有专门的硬件.

主要方法:

  • 开发了一个利用比例规律和架构启发式测试来提高测量的框架.
  • 在204张标记的室内图像上训练模型,在500个时代中进行数据增强.
  • 实施冗余校正方法以减少距离偏差错误.

主要成果:

  • 实现了0.995的平均平均精度 (mAP@50),0.995的精度和0.992的回忆,表明模型的融合和概括.
  • 冗余校正方法将距离偏差误差减少到大约10%,平均绝对误差在使用案例中低于2%.
  • 该解决方案运行在2D视觉输入上,允许在设备上和离线使用,无需专门的硬件.

结论:

  • 拟议的框架为使用标准智能手机摄像头进行准确的室内空间测量提供了一个可扩展,低成本的替代方案.
  • 在现实室内环境中展示了基于相机的几何校正的可行性.
  • 未来的工作可能会将这种方法与多式模式模型集成在一起,用于各种应用中的全房间空间推理.