Paper
5 May 2011 Road network estimation through GMTI track fusion
Maria Scalzo, Eric Jones, Adnan Bubalo, Mark Alford, Gregory Wood
Author Affiliations +
Abstract
Road networks and associated traffic flow information are topics that have an innumerable number of applications, ranging from highway planning to military intelligence. Despite the importance of these networks, archival databases that often have update rates on the order of years or even decades have historically been the main source for obtaining and analyzing road network information. This somewhat static view of a potentially changing infrastructure can cause the information to therefore be incomplete and incorrect. Furthermore, these road databases are not only static, but rarely provide information beyond a simple two-dimensional view of a road, where divided high-ways are represented in the same manner as a rural dirt road. It is for these reasons that the use of Ground Moving Target Indicator (GMTI) data and tracks to create road networks is explored. This data lends itself to being able to not only provide a single static snapshot of a network that is considered the network for years, but to provide a consistently accurate and updated changing picture of the environment. The approach employed for creating a road network from GMTI tracks includes a technique known as Continuous Dynamic Time Warping (CDTW), as well as a general fusion routine.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Maria Scalzo, Eric Jones, Adnan Bubalo, Mark Alford, and Gregory Wood "Road network estimation through GMTI track fusion", Proc. SPIE 8050, Signal Processing, Sensor Fusion, and Target Recognition XX, 805002 (5 May 2011); https://doi.org/10.1117/12.884699
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KEYWORDS
Roads

Databases

Image processing

Distance measurement

Evolutionary algorithms

Image segmentation

Computer programming

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