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相关概念视频

Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

548
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
548
Design Example: Measuring Distance Between Two Points with Obstructions01:10

Design Example: Measuring Distance Between Two Points with Obstructions

27
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...
27
Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

38
The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
38
Design Example: Marking Boundaries of a Site Using a Compass01:12

Design Example: Marking Boundaries of a Site Using a Compass

32
Marking site boundaries using a compass is a precise surveying technique that ensures the accuracy of boundary delineation. The process begins by using provided site details, including the bearings and lengths of each boundary line. The initial step involves calculating latitudes and departures for all sides of the site. This computation verifies that the traverse is free of errors, ensuring a closed and accurate boundary.The process starts at a known point, such as Point A, which is often...
32
Common Leveling Mistakes and Errors01:17

Common Leveling Mistakes and Errors

59
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...
59
Profile Leveling and Cross Sections01:26

Profile Leveling and Cross Sections

116
Profile leveling and cross-sections are surveying methods used to determine and document terrain elevations for infrastructure projects such as highways, railroads, canals, and pipelines. These methods provide data for earthwork planning and alignment of proposed routes.  Profile leveling involves measuring elevations along a fixed line to create a vertical terrain profile. A surveyor sets up a leveling instrument at the benchmark (BM) and records a backsight (BS) to determine the...
116

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相关实验视频

Updated: Jun 3, 2025

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
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A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

Published on: January 18, 2020

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基于反向视角映射的跨场路标识检测.

Eric Hsueh-Chan Lu1, Yi-Chun Hsieh1

  • 1Department of Geomatics, National Cheng Kung University, No. 1, University Rd., Tainan 701, Taiwan.

Sensors (Basel, Switzerland)
|January 8, 2025
PubMed
概括

本研究通过使用虚拟和真实数据集来解决自动驾驶汽车道路标记检测方面的挑战. 反向视角映射显著提高了遥远和扭曲物体的检测精度.

科学领域:

  • 计算机视觉 计算机视觉
  • 自主系统 自主系统
  • 机器学习 机器学习

背景情况:

  • 自动驾驶汽车行业需要强大的道路标记检测,以确保安全运行.
  • 手动收集和标记道路标记的数据是耗时和劳动密集的.
  • 标准的物体检测模型在不同距离的小物体和不同尺度上扎.

研究的目的:

  • 为自动驾驶汽车开发更强大,更准确的道路标志检测模型.
  • 为了克服小物体检测和道路图像中视角扭曲的局限性.
  • 通过虚拟和现实世界台湾道路数据集验证模型的性能.

主要方法:

  • 利用虚拟和开源数据集的组合来训练对象检测模型.
  • 采用数据增强和同谱转换来扩展有限的数据集.
  • 应用反向视角映射 (IPM) 将前视图图像转换为鸟视图.

主要成果:

  • 数据增强和IPM显著提高了模型的稳定性和稳定性.
  • IPM技术有效地解决了"远距离的小物体"和"视角扭曲"的问题.
  • 模型测试显示,在前视图和鸟视图图像上的检测准确度有了惊人的18.62%的改善.
关键词:
跨领域的跨领域.深度学习是一种深度学习.反向视角映射反向视角映射对象检测对象检测是指对象的检测.道路标志 道路标志 道路标志

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相关实验视频

Last Updated: Jun 3, 2025

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
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A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers

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Combining Eye-tracking Data with an Analysis of Video Content from Free-viewing a Video of a Walk in an Urban Park Environment
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结论:

  • 拟议的方法结合了虚拟数据,增强和IPM,显著改善了自动驾驶汽车的道路标志检测.
  • 将图像转换为鸟视图对于克服道路场景理解中的规模和视角挑战至关重要.
  • 这种方法为开发可靠的道路标志检测系统提供了可行的解决方案,即使初始数据集有限.