Glossary Updates12 new terms added to the glossaries · October 2, 2026, 22:44 CEST
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Glossary · Machine vision

3D vision

Also known as: 3D machine vision, 3D imaging

German: 3D-Bildverarbeitung

In machine vision, 3D vision is the acquisition and evaluation of three-dimensional shape information, such as depth maps or point clouds, using methods like stereo vision, laser triangulation, structured light or time-of-flight measurement.

  • Machine vision

In one sentence

3D vision captures and evaluates depth or point-cloud data using stereo, laser triangulation, structured light or time-of-flight.

Example

3D vision measures the height of each box in a mixed pallet so the robot can pick the top boxes without prior knowledge of the layout.

How it applies

  • Engineering: The method is chosen by accuracy, speed, measuring volume and surface properties. Shiny, dark or transparent surfaces are difficult for most methods; motion of the part favors single-shot methods.
  • Commissioning: 3D sensors need calibration, often a Hand-eye calibration to the robot, and tuning of exposure and filtering. Results depend strongly on ambient light for some methods.
  • Documentation: The documentation team should state the measuring principle, the measuring range, the laser class if a laser is used, and the conditions under which results were validated.

3D vision vs. 2D vision

2D vision evaluates intensity images and finds position in a plane. 3D vision adds height and orientation, needed for bin picking, volume measurement and inspecting surface shape.

By knowledge.aitechdoc.world · Published September 26, 2026 · Last reviewed

Source: AI TechDoc Blog editorial definition, based on machine vision practice

Definitions follow the cited standards and specifications. Where a source is a copyrighted publication, such as an ISO, IEC or EN standard, the definition is a close paraphrase, not a verbatim quotation, so as not to infringe copyright. We recommend reading the original publication. The sections “How it applies” are editorial commentary by AI TechDoc Blog and are not part of any standard.

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