Expanding on the BRIAR Dataset: A Comprehensive Whole Body Biometric Recognition Resource at Extreme Distances and Real-World Scenarios (Collections 1-4)

TL;DR

This paper introduces an extended biometric recognition dataset designed for extreme distances and real-world scenarios, addressing current limitations in biometric identification technology.

Contribution

It provides a comprehensive new dataset with detailed collection, curation, and annotation methods for challenging biometric recognition environments.

Findings

Enhanced dataset for extreme distance recognition

Improved understanding of biometric performance in real-world scenarios

Foundation for developing more robust biometric algorithms

Abstract

The state-of-the-art in biometric recognition algorithms and operational systems has advanced quickly in recent years providing high accuracy and robustness in more challenging collection environments and consumer applications. However, the technology still suffers greatly when applied to non-conventional settings such as those seen when performing identification at extreme distances or from elevated cameras on buildings or mounted to UAVs. This paper summarizes an extension to the largest dataset currently focused on addressing these operational challenges, and describes its composition as well as methodologies of collection, curation, and annotation.