Výsledky vyhledávání - "Bolme, David S."

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Long-Range Biometric Identification in Real World Scenarios: A Comprehensive Evaluation Framework Based on Missions

Autor: Aykac, Deniz, Brogan, Joel, Barber, Nell, Shivers, Ryan, Zhang, Bob, Sacca, Dallas, Tipton, Ryan, Jager, Gavin, Garret, Austin, Love, Matthew, Goddard, Jim, Cornett III, David, Bolme, David S.

The considerable body of data available for evaluating biometric recognition systems in Research and Development (R\&D) environments has contributed to the increasingly common problem of target performance mismatch. Biometric algorithms are frequentl

Externí odkaz: http://arxiv.org/abs/2409.01540

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From Data to Insights: A Covariate Analysis of the IARPA BRIAR Dataset for Multimodal Biometric Recognition Algorithms at Altitude and Range

Autor: Bolme, David S., Aykac, Deniz, Shivers, Ryan, Brogan, Joel, Barber, Nell, Zhang, Bob, Davies, Laura, Cornett III, David

This paper examines covariate effects on fused whole body biometrics performance in the IARPA BRIAR dataset, specifically focusing on UAV platforms, elevated positions, and distances up to 1000 meters. The dataset includes outdoor videos compared wit

Externí odkaz: http://arxiv.org/abs/2409.01514

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Expanding Accurate Person Recognition to New Altitudes and Ranges: The BRIAR Dataset

Face recognition technology has advanced significantly in recent years due largely to the availability of large and increasingly complex training datasets for use in deep learning models. These datasets, however, typically comprise images scraped fro

Externí odkaz: http://arxiv.org/abs/2211.01917

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The Mertens Unrolled Network (MU-Net): A High Dynamic Range Fusion Neural Network for Through the Windshield Driver Recognition

Autor: Ruby, Max, Bolme, David S., Brogan, Joel, Cornett III, David, Delgado, Baldemar, Jager, Gavin, Johnson, Christi, Martinez-Mendoza, Jose, Santos-Villalobos, Hector, Srinivas, Nisha

Face recognition of vehicle occupants through windshields in unconstrained environments poses a number of unique challenges ranging from glare, poor illumination, driver pose and motion blur. In this paper, we further develop the hardware and softwar

Externí odkaz: http://arxiv.org/abs/2002.12257

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Evaluating the Effectiveness of Automated Identity Masking (AIM) Methods with Human Perception and a Deep Convolutional Neural Network (CNN)

Autor: Orsten-Hooge, Kimberley D., Baragchizadeh, Asal, Karnowski, Thomas P., Bolme, David S., Ferrell, Regina, Jesudasen, Parisa R., Castillo, Carlos D., O'Toole, Alice J.

Face de-identification algorithms have been developed in response to the prevalent use of public video recordings and surveillance cameras. Here, we evaluated the success of identity masking in the context of monitoring drivers as they actively opera

Externí odkaz: http://arxiv.org/abs/1902.06967

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