Dr. Brian J. Daniel Profile

Dr. Brian J. Daniel

Senior Image Scientist

SPIE Involvement:

Author

Proceedings Article | 14 June 2023 Paper

Multi-agent collaboration environment simulation

Joshua Haley, Jonathan Tucker, Jonathan Nesper, Brian Daniel, Trisha Fish

Proceedings Volume 12529, 125290P (2023) https://doi.org/10.1117/12.2663828

KEYWORDS: Data modeling, Object detection, Device simulation, Sensors, Infrared sensors, Electro optical modeling, Computer simulations, Environmental sensing

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Machine Learning (ML) and Artificial intelligence (AI) have increased automation potential within defense applications such as border protection, compound security, and surveillance applications. Advances in low-size weight and power (SWAP) computing platforms and unmanned aerial systems (UAS) have enabled autonomous systems to meet the critical needs of future defense systems. Recent academic advances in deep learning aided computer vision yielding impressive results on object detection and recognition, necessary capabilities to enable autonomy in defense applications. These advances, often open-sourced, enable the opportunistic integration of state-of-the-art (SOTA) algorithms. However, these systems require a large amount of object-relevant data to transfer from general academic domains to more relevant situations. Additionally, UAS systems require costly verification and validation of autonomy logic. These challenges can lead to high costs for both training data generation and costly field autonomy integration and testing activities. To address these challenges, in conjunction with partners, Elbit America has developed a multipurpose synthetic simulation environment capable of generating synthetic training data and prototyping, verifying, and validating autonomous distributed behaviors. We integrated a thermal modeling capability into Unreal Engine to create realistic training data by enabling the real-time simulation of SWIR, MWIR, and LWIR sensors. This radiometrically correct sensor model capability enables the simulation-based training data generation for our object recognition and classification pipeline, called Rapid Algorithm Development and Deployment (RADD). Several drones were instantiated using emulated flight controllers to enable end-to-end autonomy training and development before hardware availability. Herein, we describe an overview of the simulation environment and its relevance to detection, classification, and distributed autonomous decision-making.

Proceedings Article | 18 May 2013 Paper

The SHARE 2012 data campaign

AnneMarie Giannandrea, Nina Raqueno, David Messinger, Jason Faulring, John Kerekes, Jan van Aardt, Kelly Canham, Shea Hagstrom, Erin Ontiveros, Aaron Gerace, Jason Kaufman, Karmon Vongsy, Heather Griffith, Brent Bartlett, Emmett Ientilucci, Joseph Meola, Lauwrence Scarff, Brian Daniel

Proceedings Volume 8743, 87430F (2013) https://doi.org/10.1117/12.2015935

KEYWORDS: Sensors, Target detection, LIDAR, Aerospace engineering, Imaging systems, Electroluminescent displays, Remote sensing, Hyperspectral imaging, Image sensors, Satellites

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Proceedings Article | 18 May 2013 Paper

Automatic ship detection from commercial multispectral satellite imagery

Brian Daniel, Alan Schaum, Eric Allman, Robert Leathers, Trijntje Downes

Proceedings Volume 8743, 874312 (2013) https://doi.org/10.1117/12.2017762

KEYWORDS: Clouds, Multispectral imaging, Sensors, Neodymium, Satellite communications, Satellites, Detection and tracking algorithms, Image fusion, Satellite imaging, Earth observing sensors

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SPIE Journal Paper | 8 August 2012

Continuum fusion methods of spectral detection

Alan Schaum, Brian Daniel

OE, Vol. 51, Issue 11, 111718, (August 2012) https://doi.org/10.1117/12.10.1117/1.OE.51.11.111718

KEYWORDS: Sensors, Target detection, Detection and tracking algorithms, Data modeling, Lawrencium, Affine motion model, Optical engineering, Hyperspectral systems, Hyperspectral target detection, Statistical analysis

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Proceedings Article | 3 May 2012 Paper

Autonomous cross-correlation of optical MTI for live inspection and tracking

Jason Edelberg, Brian Daniel, Michael Wilson, Steve Frawley, Chris Meadows, Troy Johnson, Michael Duncan

Proceedings Volume 8396, 839609 (2012) https://doi.org/10.1117/12.921289

KEYWORDS: Sensors, Surveillance, Image processing, Analytical research, Motion detection, Image compression, Infrared sensors, Inspection, Optical tracking, Intelligence systems

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Proceedings Article | 26 May 2011 Paper

Autonomous collection of dynamically-cued multi-sensor imagery

Brian Daniel, Michael Wilson, Jason Edelberg, Mark Jensen, Troy Johnson, Scott Anderson

Proceedings Volume 8020, 80200A (2011) https://doi.org/10.1117/12.882926

KEYWORDS: Sensors, Image sensors, Inspection, Surveillance, Synthetic aperture radar, Target detection, Mid-IR, Databases, High altitude reconnaissance, Infrared sensors

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Proceedings Article | 20 May 2011 Paper

Linear log-likelihood ratio (L3R) algorithm for spectral target detection

Brian Daniel, Alan Schaum

Proceedings Volume 8048, 804804 (2011) https://doi.org/10.1117/12.884337

KEYWORDS: Detection and tracking algorithms, Target detection, RGB color model, Linear filtering, Human-machine interfaces, Hyperspectral imaging, Palladium, Analytical research, Gaussian filters, Hyperspectral target detection

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Proceedings Article | 11 May 2011 Paper

Next generation signature-based hyperspectral detection: a challenge to atmospheric modelers

A. Schaum, Brian Daniel

Proceedings Volume 8040, 80400C (2011) https://doi.org/10.1117/12.883506

KEYWORDS: Target detection, Sensors, Detection and tracking algorithms, Atmospheric modeling, Hyperspectral target detection, Atmospheric sensing, Algorithm development, Visualization, Reflectivity, Systems modeling

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Proceedings Article | 13 May 2010 Paper

Urchin: an RX-derivative accounting for anisotropies in whitened clutter

Brian Daniel, Alan Schaum

Proceedings Volume 7695, 769504 (2010) https://doi.org/10.1117/12.850222

KEYWORDS: Anisotropy, Target detection, Detection and tracking algorithms, Hyperspectral imaging, Data modeling, Mahalanobis distance, Palladium, Analytical research, Detection theory, Spherical lenses

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Proceedings Article | 15 April 2008 Paper

Phase retrieval in sparse aperture systems with phase diversity: a trade space study

Brian Daniel, Matthew Bolcar, John Schott, James Fienup

Proceedings Volume 6958, 69580K (2008) https://doi.org/10.1117/12.782191

KEYWORDS: Signal to noise ratio, Point spread functions, Sensors, Remote sensing, RGB color model, Phase retrieval, Space telescopes, Telescopes, Optical transfer functions, Mirrors

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Showing 5 of 10 publications

Conference Committee Involvement (4)

Geospatial Informatics, Fusion, and Motion Video Analytics V

20 April 2015 | Baltimore, MD, United States

Geospatial InfoFusion and Video Analytics IV

5 May 2014 | Baltimore, MD, United States

Geospatial InfoFusion III

2 May 2013 | Baltimore, Maryland, United States

Geospatial InfoFusion II

26 April 2012 | Baltimore, Maryland, United States

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