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17 May 2016 A baseline for the scene understanding challenge problem
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A Scene Understanding Challenge Problem was released by AFRL at this conference in 2015 in response to DARPA’s Mathematics, Sensing, Exploitation, and Execution (MSEE) program. We consider a scene understanding system as a generalization of typical sensor exploitation systems where instead of performing a narrowly defined task (e.g., detect, track, classify, etc.), the system can perform general user-defined tasks specified in a query language. That paper1 laid out the general challenges and methods for developing scene understanding performance models. This is an enormously challenging problem, so now AFRL is illustrating the methods with a baseline system primarily developed by the University of California, Los Angeles (UCLA) during the MSEE program. This system will be publicly available for others to utilize, compare, and contrast with related methods. This paper will further explain and provide insights into the challenges, illustrating them with examples from a publicly available data set. Our intent is that these tools will relieve the requirement for developing an entire system and enable progress to occur by focusing on individual elements of the system. Finally, we will provide details as to how interested researchers may obtain the system and the data.
© (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Gregory Arnold, Jared L. Culbertson, Todd V. Rovito, Euvondia Barto, Mary Ann Harrison, and Stephen Walls "A baseline for the scene understanding challenge problem", Proc. SPIE 9842, Signal Processing, Sensor/Information Fusion, and Target Recognition XXV, 98420X (17 May 2016);


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