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Visual Object Tracking in First Person Vision.

Matteo Dunnhofer1, Antonino Furnari2, Giovanni Maria Farinella2

  • 1Machine Learning and Perception Lab, University of Udine, Via delle Scienze 206, 33100 Udine, Italy.

International Journal of Computer Vision
|January 10, 2023
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Summary
This summary is machine-generated.

This study systematically analyzes 42 visual tracking algorithms for first-person vision (FPV) tasks. Results show current trackers face challenges in FPV, but offer benefits for short-term object tracking applications.

Keywords:
Egocentric visionFirst person visionSingle object trackingVisual object tracking

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Area of Science:

  • Computer Vision
  • Human-Object Interaction Analysis

Background:

  • Understanding human-object interactions is crucial in First Person Vision (FPV).
  • Visual tracking algorithms aid in modeling these interactions by following manipulated objects.
  • Existing research lacks a methodical analysis of state-of-the-art trackers in the FPV domain.

Purpose of the Study:

  • To systematically investigate the performance of single object tracking algorithms in FPV.
  • To determine if current visual trackers can be used off-the-shelf or require domain-specific adaptations.
  • To identify challenges and potential research directions for FPV tracking.

Main Methods:

  • Comprehensive performance analysis of 42 algorithms, including generic and FPV-specific trackers.
  • Evaluation across various FPV aspects with new performance measures.
  • Introduction of TREK-150, a novel benchmark dataset with 150 annotated video sequences.

Main Results:

  • Object tracking in FPV presents unique challenges for current visual trackers.
  • Identified key factors contributing to tracking difficulties in FPV.
  • Demonstrated that trackers provide benefits for FPV tasks requiring short-term object tracking.

Conclusions:

  • Current generic object trackers face significant challenges in FPV settings.
  • Domain-specific investigations and new methodologies are needed for FPV tracking.
  • Visual trackers are valuable for specific FPV downstream tasks, with potential for increased adoption.