How it works

Stereo Vision

3D-Vision-Technology-Stereo-Vision

Stereo Vision

Principles

  • Mimicking human vision.
  • Two or more cameras.
  • Triangulation. Find corresponding points in each camera.
  • Disparity is proportional to depth.

Key considerations

  • Passive, no active lighting required.
  • Long range and outdoor usage.
  • Sensitive to flat texture-less scenes.
  • Less suitable for dense point cloud representations.
  • Region based correspondence, block averaging.
  • Look out for correspondence problem.

 

3D Vision Technology - Active Stereo Vision - Zivid

Active Stereo Vision

Principles

  • Same as stereo vision.
  • Additional random pattern projector (RPP).
  • Mimicking human vision.

Key considerations

  • Same as stereo vision, but active source.
  • Shorter range
  • Sensitive to ambient / sunlight.
  • No texture on surfaces required.
  • Solves correspondence problem.

 

Compare stereo and structured light vision point clouds.

Stereo- and active stereo cameras are often used by AI algorithms in bin-picking applications. Here are examples of a stereo camera point cloud and the same scene captured with a time-coded structured-light camera (like Zivid). 

 

Keep learning!

Read the whole article about active and passive 3D vision principles here, including stereo, active stereo, laser, ToF, and structured light machine vision.

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