Expanding on the BRIAR Dataset: A Comprehensive Whole Body Biometric Recognition Resource at Extreme Distances and Real-World Scenarios (Collections 1-4)
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arXiv
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866910814640799744 |
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| author | Jager, Gavin Cornett III, David Glenn, Gavin Aykac, Deniz Johnson, Christi Zhang, Robert Shivers, Ryan Bolme, David Davies, Laura Dolvin, Scott Barber, Nell Brogan, Joel Burchfield, Nick Dukes, Carl Duncan, Andrew Ferrell, Regina Garrett, Austin Goddard, Jim Hines, Jairus Murphy, Bart Pharris, Sean Stockwell, Brandon Thompson, Leanne Yohe, Matthew |
| author_facet | Jager, Gavin Cornett III, David Glenn, Gavin Aykac, Deniz Johnson, Christi Zhang, Robert Shivers, Ryan Bolme, David Davies, Laura Dolvin, Scott Barber, Nell Brogan, Joel Burchfield, Nick Dukes, Carl Duncan, Andrew Ferrell, Regina Garrett, Austin Goddard, Jim Hines, Jairus Murphy, Bart Pharris, Sean Stockwell, Brandon Thompson, Leanne Yohe, Matthew |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_14070 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Expanding on the BRIAR Dataset: A Comprehensive Whole Body Biometric Recognition Resource at Extreme Distances and Real-World Scenarios (Collections 1-4) Jager, Gavin Cornett III, David Glenn, Gavin Aykac, Deniz Johnson, Christi Zhang, Robert Shivers, Ryan Bolme, David Davies, Laura Dolvin, Scott Barber, Nell Brogan, Joel Burchfield, Nick Dukes, Carl Duncan, Andrew Ferrell, Regina Garrett, Austin Goddard, Jim Hines, Jairus Murphy, Bart Pharris, Sean Stockwell, Brandon Thompson, Leanne Yohe, Matthew Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning 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. |
| title | Expanding on the BRIAR Dataset: A Comprehensive Whole Body Biometric Recognition Resource at Extreme Distances and Real-World Scenarios (Collections 1-4) |
| topic | Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning |
| url | https://arxiv.org/abs/2501.14070 |