SBIR/STTR Award attributes
The demand for 3D LADAR imaging is growing both in the DoD and commercial sectors. However, exploitation processes and tools have lagged advances in LADAR technologies. In a prior Phase II SBIR effort, 361 Interactive leveraged a Cognitive Systems Engineering approach to develop a LADAR analysis tool that was implemented as a Quick Terrain Modeler plug-in. The tool consisted of automated feature extraction and machine learning-based object classification algorithms along with a novel user interface for interacting with the algorithms and their output. The current effort will build upon that prototype product to expand and enhance both the algorithm and UI capabilities. Our overall objective for this Phase II follow-on effort is to develop a mission-driven, analyst-centric LADAR analysis capability that fosters human-machine teaming to improve the accuracy, efficiency and effectiveness of the LADAR exploitation workflow. We will employ a user-centric approach involving frequent and substantive interaction with end users, and incorporation of state-of-the-art machine learning algorithms to segment and classify LADAR data sets. The final product will seamlessly integrate into the analyst’s workflow, provide much better accuracy, and significantly expand the range of classes and subclasses that can be detected.
