{"title":"Model Analysis Geometry Imagery Correlation Tool Kit (MAGIC-TK) for Model Development and Image Analysis","authors":"T. Taczak, M. Rundquist, Colin P. Cahill","doi":"10.1109/AIPR.2006.26","DOIUrl":null,"url":null,"abstract":"The application of IR signature prediction codes in DoD has been predominantly in two areas: 1.) the development of total signature requirements under a broad set of environmental and operational conditions and 2.) the evaluation of signatures of vessels and signature treatments to ensure the specifications are met. As computing power and IR scene generation techniques have advanced, simulation capabilities have evolved to scene injection into real hardware systems. To capture the real world effects required to accurately analyze search and track algorithms, the fidelity of the complete IR scene has required improvement. New validation methodologies are required to evaluate the accuracy of advanced IR scene generation models. This paper will review some of the approaches incorporated into a new model validation tool that will be able to verify model inputs and quantitatively evaluate differences between measured and predicted imagery.","PeriodicalId":375571,"journal":{"name":"35th IEEE Applied Imagery and Pattern Recognition Workshop (AIPR'06)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2006-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"35th IEEE Applied Imagery and Pattern Recognition Workshop (AIPR'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIPR.2006.26","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The application of IR signature prediction codes in DoD has been predominantly in two areas: 1.) the development of total signature requirements under a broad set of environmental and operational conditions and 2.) the evaluation of signatures of vessels and signature treatments to ensure the specifications are met. As computing power and IR scene generation techniques have advanced, simulation capabilities have evolved to scene injection into real hardware systems. To capture the real world effects required to accurately analyze search and track algorithms, the fidelity of the complete IR scene has required improvement. New validation methodologies are required to evaluate the accuracy of advanced IR scene generation models. This paper will review some of the approaches incorporated into a new model validation tool that will be able to verify model inputs and quantitatively evaluate differences between measured and predicted imagery.