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Accession Number ADA586168
Title Model Classes, Approximation, and Metrics for Dynamic Processing of Urban Terrain Data.
Publication Date 2013
Media Count 67p
Personal Author A. Kurdila R. Baraniuk R. DeVore S. Kulkarni S. Osher
Abstract Theory, algorithms, and software have been developed for the analysis and processing of point cloud sensor data for representation, analysis and visualization of complex urban terrain. These involve various parameterizations of terrain data based on implicit surface representations and adaptive multiscale methods that enable high resolution and enhance understanding of topology and geometric features. The wavelet and multi scale methods enable fast computation and allow for varying local resolution of the data depending on the local density of the point cloud. The implicit representations which are developed facilitate highly accurate approximation of signed distances to the sensed terrain surface. The level sets of the signed distance provide efficiently computed field of view from specified observation points. Collaboration among MURI focus groups has yielded hybrid methods incorporating the best features of both approaches. Simulation and field experiments have been conducted to test the MURI methodologies. These include problems of sensor assimilation for autonomous navigation of urban terrain, surveillance, secure route planning, line of sight, target acquisition and a host of related problems.
Keywords Algorithms
Approximation theories
Computer programs
Dynamic processing
Implicit methods
Level sets
Multi resolutions
Point cloud sensor data
Urban areas

Source Agency Non Paid ADAS
NTIS Subject Category 92C - Social Concerns
72B - Algebra, Analysis, Geometry, & Mathematical Logic
Corporate Author South Carolina Univ., Columbia. Research Foundation.
Document Type Technical report
Title Note Final annual rept. no. 5, 1 May 2007-30 Sep 2008.
NTIS Issue Number 1405
Contract Number W911NF-07-1-0185

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