The production of geospatial information from overhead imagery is generally a labor-intensive process. Analysts must accurately delineate and extract important features, such as buildings, roads, and landcover from the imagery. Automated Feature Extraction (AFE) tools offer the prospect of reducing analyst's workload. This paper presents a new tool, called iMVS, for extracting buildings and discusses user testing conducted by the National GeospatialIntelligence Agency (NGA). Using a semiautomated approach, iMVS processes two or more images to form a set of hypothesized 3-D buildings. When the user clicks on one of the building vertices, the system determines which hypothesis is the best fit and extracts the building. A set of powerful editing tools support rapid clean-up of the extraction, including extraction of complex buildings. User testing of iMVS provides an assessment of the benefits and identifies areas for system improvement.
Sung Chun Lee, Keith E. Price, Ramakant Nevatia, T