Paper
14 May 2015 Qualia centric hypothetical thinking: applications to vehicle tracking with the fusion of EO and SAR input data sources
Jonathan White, Anthony Helmstetter, Jared Culbertson, Igor Ternovskiy
Author Affiliations +
Abstract
In this work, we present a novel improvement to classical vehicle tracking algorithms by implementing a three-tier architecture consisting of a data-centric vehicle tracker paired with a hypothetical thinking layer that is controlled by an overarching goal layer – this models more effectively how a human thinks about and analyzes situations like vehicle tracking. The upper two layers are disassociated from the data itself and instead operate from the idea of qualia in event space. Our proof-of-concept results show how a classical vehicle tracker can be improved by fusing multiple input sources using coincident SAR and EO data paired with a thinking layer that is able to detect, hypothesize, and resolve conflicts.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jonathan White, Anthony Helmstetter, Jared Culbertson, and Igor Ternovskiy "Qualia centric hypothetical thinking: applications to vehicle tracking with the fusion of EO and SAR input data sources", Proc. SPIE 9458, Cyber Sensing 2015, 945806 (14 May 2015); https://doi.org/10.1117/12.2176582
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Cited by 1 scholarly publication.
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KEYWORDS
Synthetic aperture radar

Data modeling

Sensors

Detection and tracking algorithms

Roads

Data fusion

Device simulation

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