Intelligent Data Fusion for Wide-Area Assessment of UXO Contamination

2008 ◽  
Author(s):  
Susan L. Rose-Pehrsson ◽  
Kevin Johnson ◽  
Christian Minor ◽  
Verner Guthrie
Keyword(s):  
2007 ◽  
Author(s):  
Susan L. Rose-Pehrsson ◽  
Kevin Johnson ◽  
Christian Minor ◽  
Verner Guthrie
Keyword(s):  

2010 ◽  
Author(s):  
Wolfgang Koch ◽  
Martin Ulmke ◽  
Joachim Biermann ◽  
Marion Sielemann

Author(s):  
M. Tuceryan

This article describes a software framework for realizing such a distributed tracking environment by discovering independently deployed, possibly heterogeneous trackers and fusing the data from them while roaming over a wide area. In addition to the MAR domain, this kind of a tracking capability would also be useful in other domains such as robotics and location-aware applications. The novelty of this research lies in the amalgamation of the theoretical principles from the domains of AR/VR, data fusion, and the distributed software systems to create a sensor-based, wide-area tracking environment.


2008 ◽  
Vol 23 (2) ◽  
pp. 237-252 ◽  
Author(s):  
Kevin J. Johnson ◽  
Christian P. Minor ◽  
Verner N. Guthrie ◽  
Susan L. Rose-Pehrsson
Keyword(s):  

2014 ◽  
Vol 42 (3-4) ◽  
pp. 396-407 ◽  
Author(s):  
Arturo R. Messina ◽  
Noe Reyes ◽  
Ismael Moreno ◽  
Marco A. Pérez G.

Author(s):  
A. Polychronopoulos ◽  
N. Floudas ◽  
A. Amditis ◽  
D. Bank ◽  
B. van den Broek

Author(s):  
D. E. Becker

An efficient, robust, and widely-applicable technique is presented for computational synthesis of high-resolution, wide-area images of a specimen from a series of overlapping partial views. This technique can also be used to combine the results of various forms of image analysis, such as segmentation, automated cell counting, deblurring, and neuron tracing, to generate representations that are equivalent to processing the large wide-area image, rather than the individual partial views. This can be a first step towards quantitation of the higher-level tissue architecture. The computational approach overcomes mechanical limitations, such as hysterisis and backlash, of microscope stages. It also automates a procedure that is currently done manually. One application is the high-resolution visualization and/or quantitation of large batches of specimens that are much wider than the field of view of the microscope.The automated montage synthesis begins by computing a concise set of landmark points for each partial view. The type of landmarks used can vary greatly depending on the images of interest. In many cases, image analysis performed on each data set can provide useful landmarks. Even when no such “natural” landmarks are available, image processing can often provide useful landmarks.


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