Media.Player

Correlate Imaging for Simulation-Based Training Systems

技術優勢

Determines differences between images

技術應用

Military training Distributed learning Simulation systems

詳細技術說明

The algorithm provides a quantitative, automated method for assessing the correlation level of two rendered images. By calibrating the algorithm with results from human-in-the-loop testing, software developed using this algorithm can improve image correlation to the point where differences are undetectable by a human observer while using minimal computing resources.

*Abstract

Military and private companies are increasingly investing in virtual environments, simulation-based training, specialized simulation platforms for collective team training, and live-virtual-constructive training. Consistency, and with it the look and feel that makes simulated training most effective, can be effected when imaging renders differently for individual trainees because systems lack a uniform image generation process. Conventionally, correlation and interoperability between simulation systems can be determined by terrain database (TDB) correlation methods and/or human comparison. However, the TDB is limited by manufacturersΓÇÖ proprietary information within applications, which allow database correlation or synthesis but not uniform image generation processes.Researchers at UCF, in partnership with the US Army, have developed a method for visual correlation within networked simulation-based training systems. This algorithm for identifying differences between two images can be implemented as software within existing and cutting-edge simulation systems used in human-in-the-loop simulators, distributed learning, and training applications.

*Principal Investigation

Name: Daniel Barber, Ph.D.

Department:

Name: Joseph Fanfarelli

Department:

Name: Stephanie Lackey, Ph.D.

Department:

Name: Eric Ortiz

Department:

國家/地區

美國