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

Conference · Thu May 01 04:00:00 EDT 2025

DOI:https://doi.org/10.1109/FG61629.2025.11099141· OSTI ID:3002863

Cornett, David ^[1]; Glenn, Gavin ^[1]; Aykac, Deniz ^[1]; Johnson, Christi ^[1]; Zhang, Bob ^[1]; Shivers, Ryan ^[1]; Bolme, David ^[1]; Davies, Laura ^[1]; Dolvin, Scott ^[1]; Barber, Nell ^[1]; Brogan, Joel ^[1]; Burchfield, Nicholas ^[1]; Dukes, Carl Lee ^[1]; Duncan, Andrew ^[1]; Ferrell, Regina ^[1]; Garrett, Austin ^[1]; Goddard Jr, James ^[1]; Hines, Jairus ^[1]; Murphy, Bart ^[1]; Pharris, Sean ^[1] ; Stockwell, Brandon ^[1]; Thompson, Leanne ^[1]; Yohe, Matt ^[1]

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1. ORNL

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.

• Research Organization: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: AC05-00OR22725
• OSTI ID: 3002863
• Country of Publication: United States
• Language: English