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Updated: Sep 13, 2025

A Methodology for Capturing Joint Visual Attention Using Mobile Eye-Trackers
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Robust and enhanced 360° visual tracking based on dynamic gnomonic projection.

Hao Peng1, Yun Zhang2, Fang-Lue Zhang1

  • 1School of Engineering and Computer Science, Victoria University of Wellington, Wellington, New Zealand.

Journal of the Royal Society of New Zealand
|August 4, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel two-part method for 360-degree visual tracking, addressing distortion issues in equirectangular videos. The approach enhances existing 2D tracking algorithms for more robust and accurate 360-degree object tracking.

Keywords:
360-degreeequirectangulargnomonicrobusttracking

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Area of Science:

  • Computer Vision
  • Video Processing
  • Immersive Technologies

Background:

  • 360-degree visual tracking is crucial for immersive video processing.
  • Existing 2D tracking methods struggle with 360-degree video distortions like stretching and object deformation due to equirectangular projection.
  • A universal and effective method for 360-degree visual tracking is lacking.

Purpose of the Study:

  • To propose a novel two-part method for robust and efficient 360-degree visual tracking.
  • To adapt existing 2D visual tracking algorithms for 360-degree video analysis.
  • To improve tracking accuracy and robustness by mitigating image distortion and object deformation.

Main Methods:

  • A general method converting equirectangular images to 2D gnomonic projections, enabling integration with existing 2D trackers.
  • An enhanced tracking approach building on the UPDT algorithm, incorporating robustness and efficiency improvements.
  • A fallback mechanism combining sample set results and trajectory prediction for degraded tracking performance.

Main Results:

  • The proposed method effectively mitigates distortion issues inherent in 360-degree equirectangular representations.
  • Experimental results on two datasets demonstrate the effectiveness and advantages of the proposed 360-degree visual tracking approach.
  • The method shows potential for applications in 360-degree video editing, enabling automatic manipulation of moving objects.

Conclusions:

  • The developed two-part method offers a significant advancement in 360-degree visual tracking.
  • The approach successfully addresses the challenges of image distortion and object deformation in 360-degree videos.
  • The proposed technique has practical implications for enhancing 360-degree video processing and editing.