Lukes - 10
Much of the progress to date in scene analysis and machine vision has been accomplished independently
or in small groups. Results are typically shared in the research literature or technical symposia. There are
additional opportunities to accelerate and amplify efforts in cartographic image understanding through more
extensive collaborative efforts utilizing rapidly expanding networking technology.
6 Concluding Remarks
This paper discusses the potential to support the generation of specialized and timely spatial data for Advanced
Distributed Simulation through applied research and development activities in cartographic image understanding.
Successful insertion of automated processes in baseline data base generation and maintenance systems can have
a profound impact on the utility, productivity, flexibility and timeliness of cartographic compilation in support
of a broad spectrum of end-users including modeling and simulation.
7 REFERENCES
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ronment data representation and interchange specification (SEDRIS). In 12th Workshop on Standards for the
Interoperability of Distributed Simulations. Institute for Simulation and Training, Univ. of Central Florida,
March 1995.
[2] DIS-Committee. The DIS Vision. Technical Report IST-SP-94-01, Institute for Simulation and Training,
Univ. of Central Florida, May 1994.
[3] F. Mamaghani. Creation and usage of synthetic environments in realtime networked interactive simulation.
In Integrating Photogrammetric Techniques with Scene Analysts and Machine Vision II, volume 2486, pages
186-195. Society of Photo-Optical Instrumentation Engineers, 1995.
[4] F. Raye Norvelle. Stereo correlation: Window shaping and DEM corrections. Photogrammetric Engineering
and Remote Sensing, 58( 1): 111—115, January 1992.
[5] Michael F. Polis, Stephen J. Gifford, and David M. McKeown, Jr. Automating the construction of large scale
virtual worlds. IEEE Computer, 28(7):57-65, July 1995.
