Geospatial-Temporal Semantic Graphs for Automated Wide-Area Search
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
- Univ. of Vermont, Burlington, VT (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Univ. of San Francisco, CA (United States)
We address the problem of wide-area search of overhead imagery. Given a time sequence of overhead images, we construct a geospatial-temporal semantic graph, which expresses the complex continuous information in the overhead images in a discrete searchable form, including explicit modeling of changes seen from one image to the next. We can then express desired search goals as a template graph, and search for matches using simple and efficient graph search algorithms. This produces a set of potential matches which provide cues for where to examine the imagery in detail, applying human expertise to determine which matches are correct. We include a match quality metric that scores the matches according to how well they match the stated search goal. This enables matches to be presented in sorted order with the best matches first, similar to the results returned by a web search engine. We present an evaluation of the method applied to several examples and data sets, and show that it can be used successfully for some problems. We also remark on several limitations of the method and note additional work needed to improve its scope and robustness. Approved for public release; further dissemination unlimited.
- Research Organization:
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation
- DOE Contract Number:
- AC04-94AL85000; NA0003525
- OSTI ID:
- 1527318
- Report Number(s):
- SAND-2017-8687; 663068
- Country of Publication:
- United States
- Language:
- English
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