JOURNAL ARTICLE

Semi-automated 3-D Building Extraction from Stereo Imagery

Sung Chun LeeKeith PriceRam NevatiaTom HeinzeJohn M. Irvine

Year: 2006 Journal:   Proceedings Pages: 34-34   Publisher: Institute of Electrical and Electronics Engineers

Abstract

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 Geospatial-Intelligence Agency (NGA). Using a semi-automated 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.

Keywords:
Geospatial analysis Computer science Workload Process (computing) Set (abstract data type) Feature extraction Remote sensing Artificial intelligence Geology Operating system

Metrics

1
Cited By
0.70
FWCI (Field Weighted Citation Impact)
3
Refs
0.77
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Automated Road and Building Extraction
Physical Sciences →  Engineering →  Ocean Engineering
Remote Sensing and LiDAR Applications
Physical Sciences →  Environmental Science →  Environmental Engineering
Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology

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