Poster + Paper
12 April 2021 Penetrating radar combined with 3-D imaging for real-time augmented reality sensing and classification
Author Affiliations +
Conference Poster
Abstract
This paper presents research on the use of penetrating radar combined with 3-D computer vision for real-time augmented reality enabled target sensing. Small scale radar systems face the issue that positioning systems are inaccurate, non-portable or challenged by poor GPS signals. The addition of modern computer vision to current cutting-edge penetrating radar technology expands the common 2-D imaging plane to 6 degrees of freedom. Applying the fact that the radar scan itself is a vector with length equivalent to depth from the transmitting and receiving antennae, these technologies used in conjunction can generate an accurate 3-D model of the internal structure of any material for which radar can penetrate. The same computer vision device that localizes the radar data can also be used as the basis for an augmented reality system. Augmented reality radar technology has applications in threat detection (human through-wall, IED, landmine) as well as civil (wall and floor structure, buried item detection). For this project, the goal is to create a data registration pipeline and display the radar scan data visually in a 3-D environment using localization from a computer vision tracking device. Processed radar traces are overlayed in real time to an augmented reality screen where the user can view the radar signal intensity to identify and classify targets.
© (2021) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Joshua Girard, Dylan Burns, Dryver Huston, and Tian Xia "Penetrating radar combined with 3-D imaging for real-time augmented reality sensing and classification", Proc. SPIE 11759, Virtual, Augmented, and Mixed Reality (XR) Technology for Multi-Domain Operations II, 117590N (12 April 2021); https://doi.org/10.1117/12.2587703
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KEYWORDS
Radar

Augmented reality

3D surface sensing

Computer vision technology

Machine vision

Stereoscopy

3D vision

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