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Related Experiment Video

Updated: Jun 11, 2026

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

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

Published on: January 18, 2020

Enhanced visual object tracking in division-of-focal-plane imagery using a joint polarization descriptor.

Muhammet Özbay, Yakup Özkazanç

|June 10, 2026

Summary

This summary is machine-generated.

This study introduces the joint histogram of AoLP and DoLP (JHAD) for real-time polarization object tracking. JHAD improves tracking accuracy and robustness by jointly modeling polarization magnitude and orientation.

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Area of Science:

Computer Vision
Optical Engineering
Robotics

Background:

Polarization imaging offers richer scene information than intensity images, crucial for surface geometry and material analysis.
Existing polarization descriptors for division-of-focal-plane (DoFP) cameras often overlook the combined information of angle of linear polarization (AoLP) and degree of linear polarization (DoLP).

Purpose of the Study:

To introduce a novel polarization feature descriptor, the joint histogram of AoLP and DoLP (JHAD), for enhanced real-time object tracking.
To evaluate JHAD's effectiveness in DoFP imagery, particularly in challenging scenarios like heavy occlusion.

Main Methods:

Developed JHAD to model the joint distribution of AoLP and DoLP in a unified framework.
Integrated JHAD into correlation filter-based and Siamese tracking frameworks.
Created a new DoFP polarization tracking dataset with 105 sequences for benchmarking.

Main Results:

JHAD consistently improved tracking success and precision across various frameworks compared to conventional and state-of-the-art descriptors.
The descriptor maintained real-time tracking capabilities.
Experimental results validated JHAD's effectiveness in complex scenes with occlusion.

Conclusions:

Jointly modeling AoLP and DoLP via JHAD is highly effective for robust polarization-based object tracking.
JHAD offers a significant advancement for real-time applications utilizing DoFP polarization data.