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Light Acquisition02:16

Light Acquisition

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In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
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Depth Perception and Spatial Vision01:15

Depth Perception and Spatial Vision

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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.
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相关实验视频

Updated: Jan 13, 2026

High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques
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High-resolution, High-speed, Three-dimensional Video Imaging with Digital Fringe Projection Techniques

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基于边缘的结构光3D重建:原理,投影技术和深度学习集成.

Zhongyuan Zhang1,2, Hao Wang1,2, Yiming Li2

  • 1Shenzhen International Graduate School, Tsinghua University, Shenzhen 518000, China.

Sensors (Basel, Switzerland)
|October 29, 2025
PubMed
概括

本综述比较了用于扩散表面的边缘投影形计 (FPP) 和用于镜面的相位测量偏移计 (PMD). 它强调了微电机系统 (MEMS) 和深度学习,用于先进的3D重建.

关键词:
通过3D测量进行3D测量.深度学习是一种深度学习.边缘投影的概况测量方法边缘结构光结构光阶段测量偏向测量法测量法.

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Last Updated: Jan 13, 2026

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科学领域:

  • 光学和光子学 在光学和光子学.
  • 计算机视觉 计算机视觉
  • 计量学 计量学 计量学

背景情况:

  • 结构光3D重建是捕捉物体几何学的关键主动测量技术.
  • 它被广泛用于工业检查,文化遗产和虚拟现实.
  • 现有的审查往往缺乏主要的边缘基方法之间的系统比较,如边缘投影形计 (FPP) 和相位测量偏移计 (PMD).

研究的目的:

  • 为主流边缘式3D重建方法提供全面的比较分析.
  • 澄清不同投影方案 (例如数字光处理 (DLP),MEMS) 对系统性能的影响.
  • 探索深度学习与FPP和PMD的整合,以提高准确性.

主要方法:

  • 边缘投影形计 (FPP) 和相位测量偏移计 (PMD) 的系统比较.
  • 分析测量原则,系统实施,校准和错误控制.
  • 研究投影技术 (DLP,MEMS) 和深度学习集成.

主要成果:

  • 在多个技术维度中比较FPP和PMD.
  • 审查澄清了像DLP和MEMS这样的投影方案的影响.
  • 深度学习显示了提高相位检索和3D重建精度的潜力.

结论:

  • 微电机系统 (MEMS) 为轻量级,高动态范围的测量提供了潜力.
  • 深度学习正在成为增强3D重建的关键工具.
  • 未来的研究应该专注于系统建模,智能重建和性能评估.