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Related Experiment Video

Updated: May 29, 2026

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

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

Published on: January 18, 2020

A perspective on range finding techniques for computer vision.

R A Jarvis1

  • 1Department of Computer Science, Australian National University, Canberra, Australia.

IEEE Transactions on Pattern Analysis and Machine Intelligence
|August 27, 2011
PubMed
Summary
This summary is machine-generated.

This study reviews various range finding techniques for 3D object analysis. It highlights their strengths and weaknesses for computer vision applications.

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Last Updated: May 29, 2026

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
12:39

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

Published on: January 18, 2020

Area of Science:

  • Computer Vision
  • Robotics
  • 3D Sensing

Background:

  • Growing interest in 3D data acquisition for scene analysis.
  • Need for non-contact methods to determine object configurations and extents.

Purpose of the Study:

  • Survey diverse range finding approaches.
  • Analyze applicability and limitations for computer vision.

Main Methods:

  • Literature review of generalized range finding techniques.
  • Comparative analysis based on computer vision requirements.

Main Results:

  • Identification of various range finding methods.
  • Discussion of their respective advantages and disadvantages.

Conclusions:

  • Range data acquisition is crucial for advanced computer vision.
  • Understanding method limitations is key for effective 3D scene analysis.