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Zhang, Bob

Publications and source records attributed to Zhang, Bob.

7 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

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

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 with indoor images and controlled gait recordings. Normalized raw fusion scores relate directly to predicted false accept rates (FAR), offering an intuitive means for interpreting model results. A linear model is developed to predict biometric algorithm scores, analyzing their performance to identify the most influential covariates on accuracy at altitude and range. Weather factors like temperature, wind speed, solar loading, and turbulence are also investigated in this analysis. The study found that resolution and camera distance best predicted accuracy and findings can guide future research and development efforts in long-range/elevated/UAV biometrics and support the creation of more reliable and robust systems for national security and other critical domains.

Bolme, David↗
DOE OSTI2024

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

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 frequently tested against data that may not reflect the real world applications they target. From a Testing and Evaluation (T&E) standpoint, this domain mismatch causes difficulty assessing when improvements in State-of-the-Art (SOTA) research actually translate to improved applied outcomes. This problem can be addressed with thoughtful preparation of data and experimental methods to reflect specific use-cases and scenarios.To that end, this paper evaluates research solutions for identifying individuals at ranges and altitudes, which could support various application areas such as counterterrorism, protection of critical infrastructure facilities, military force protection, and border security. We address challenges including image quality issues and reliance on face recognition as the sole biometric modality. By fusing face and body features, we propose developing robust biometric systems for effective long-range identification from both the ground and steep pitch angles. Preliminary results show promising progress in whole-body recognition. This paper presents these early findings and discusses potential future directions for advancing long-range biometric identification systems based on mission-driven metrics.

Aykac, Deniz↗
DOE OSTI2023

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 from news sites or social media plat-forms and, therefore, have limited utility in more advanced security, forensics, and military applications. These applications require lower resolution, longer ranges, and ele-vated viewpoints. To meet these critical needs, we collected and curated the first and second subsets of a large multi-modal biometric dataset designed for use in the research and development (R&D) of biometric recognition technolo-gies under extremely challenging conditions. Thus far, the dataset includes more than 350,000 still images and over 1,300 hours of video footage of approximately 1,000 sub-jects. To collect this data, we used Nikon DSLR cameras, a variety of commercial surveillance cameras, specialized long-rage R&D cameras, and Group 1 and Group 2 UAV platforms. The goal is to support the development of algorithms capable of accurately recognizing people at ranges up to 1,000 m and from high angles of elevation. These ad-vances will include improvements to the state of the art in face recognition and will support new research in the area of whole-body recognition using methods based on gait and anthropometry. This paper describes methods used to col-lect and curate the dataset, and the dataset's characteristics at the current stage.

Brogan, Joel↗
DOE OSTI2022

Evaluating Efficiency and Security of Connected and Autonomous Vehicle Applications

Evaluating efficiency and security of Connected and Autonomous Vehicles (CAVs) requires an environment that can support applications and measurements under real-world conditions. This work introduces our implementation and evaluation of a Connected and Autonomous Vehicle Research Environment (CAVRE). We implement and evaluate an existing CAV application called Cooperative Adaptive Cruise Control (CACC) using physical Vehicle-to-Vehicle (V2V) communications between a virtual agent and a real autonomous vehicle operating on a steerable dynamometer. CAVRE allows the follower to autonomously control longitudinal behavior on the dynamometer in order to maintain a steady following time gap from the leader. The effects of a wireless jamming attack on CACC and fuel efficiency is also evaluated. By executing attacks in a controlled environment, we learn how compromised communications can degrade CAV applications. We show that jamming V2V communications can impact CACC’s string stability and decrease fuel efficiency by more than 50%.

Taylor, Curtis↗
DOE OSTI2020

Integrated Energy System Investigation for the Eastman Chemical Company, Kingsport, TN Facility

The industrial manufacturing industry is looking to implement new methods of energy production to ensure a consistent energy supply while reducing economic costs and environmental impacts. Much of the manufacturing industry relies on fossil fuels—primarily coal and natural gas—of which there are finite resources subject to price volatility due to an inelastic demand. These resources also come with significant negative environmental impacts related to emissions. While complete independence from fossil fuels is not immediately realistic, options are available to significantly reduce dependency on fossil fuel supplies, including integrated energy systems (IESs) which tightly couple nuclear energy source generators with energy consumers (i.e., industrial factories) to fulfill power and energy requirements. Once realized, optimized IESs may yield significant economic and environmental benefits over traditionally isolated generator and consumer facilities. This report presents a feasibility study for siting an IES to meet the steam and electricity needs of Eastman Chemical Company’s facility in Kingsport, Tennessee. This study explored reactor technology options, evaluation,and optimization,with a focus on meeting the facility’s operational and reliability requirements. This work is part of an ongoing effort by Eastman to be good environmental stewards and meet the demands of their customers by shifting to more environmentally sustainable solutions for their energy needs. Outcomes of this report are also of general interest and value to any design or development team seeking to deploy an IES,as many topics described herein are generally applicable to any nuclear power facility.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Integrated Energy System Investigation for the Eastman Chemical Company, Kingsport, Tennessee Facility

The industrial manufacturing industry is looking to implement new methods of energy production to ensure a consistent energy supply while reducing economic costs and environmental impacts. Much of the manufacturing industry relies on fossil fuels—primarily coal and natural gas—of which there are finite resources subject to price volatility due to an inelastic demand. These resources also come with significant negative environmental impacts related to emissions. While complete independence from fossil fuels is not immediately realistic, options are available to significantly reduce dependency on fossil fuel supplies, including integrated energy systems (IESs) which tightly couple nuclear energy source generators with energy consumers (i.e., industrial factories) to fulfill power and energy requirements. Once realized, optimized IESs may yield significant economic and environmental benefits over traditionally isolated generator and consumer facilities. This report presents a feasibility study for siting an IES to meet the steam and electricity needs of Eastman Chemical Company’s facility in Kingsport, Tennessee. This study explored reactor technology options, evaluation, and optimization, with a focus on meeting the facility’s operational and reliability requirements. This work is part of an ongoing effort by Eastman to be good environmental stewards and meet the demands of their customers by shifting to more environmentally sustainable solutions for their energy needs. Outcomes of this report are also of general interest and value to any design or development team seeking to deploy an IES, as many topics described herein are generally applicable to any nuclear power facility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗