Object-level change detection for autonomous sensemaking

Dominic LeDuc; Taber Fisher; Isaiah Engle; Avinash K. Vadlamudi; Matthew D. Reisman

doi:10.1117/12.2621960

27 May 2022 Object-level change detection for autonomous sensemaking

Dominic LeDuc, Taber Fisher, Isaiah Engle, Avinash K. Vadlamudi, Matthew D. Reisman

Proceedings Volume 12099, Geospatial Informatics XII; 1209909 (2022) https://doi.org/10.1117/12.2621960
Event: SPIE Defense + Commercial Sensing, 2022, Orlando, Florida, United States

Abstract

For many intelligence sources, reliable independent algorithms exist for interpreting the data and reporting relevant information to analysts. However, achieving the necessary cross-source data fusion from these sources and algorithmic outputs to achieve true sensemaking can be challenging. This is especially true at the individual object level, given the sources' highly variable spatiotemporal resolutions and uncertainties. We have developed a framework for merging automatic target recognition (ATR) algorithms and their outputs to produce a sensor-agnostic means of object level change detection to establish the necessary patterns-of-life for big picture sensemaking, activity-based intelligence, and autonomous decision making.

Conference Presentation

Citation Download Citation

Dominic LeDuc, Taber Fisher, Isaiah Engle, Avinash K. Vadlamudi, and Matthew D. Reisman "Object-level change detection for autonomous sensemaking", Proc. SPIE 12099, Geospatial Informatics XII, 1209909 (27 May 2022); https://doi.org/10.1117/12.2621960

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