#67:
C. R. Shyu,
M. Klaric,
G. J. Scott,
A. S. Barb,
C. H. Davis, and
K. Palaniappan
IEEE Trans. Geoscience Remote Sensing,
Volume 45,
pgs. 839--852,
2007
Abstract,
Bibtex,
PlainText,
PDF,
DOI,
Google Scholar
Abstract—Searching for relevant knowledge across heteroge- neous geospatial databases requires an extensive knowledge of the semantic meaning of images, a keen eye for visual patterns, and efficient strategies for collecting and analyzing data with mini- mal human intervention. In this paper, we present our recently developed content-based multimodal Geospatial Information Re- trieval and Indexing System (GeoIRIS) which includes automatic feature extraction, visual content mining from large-scale image databases, and high-dimensional database indexing for fast re- trieval. Using these underpinnings, we have developed techniques for complex queries that merge information from heterogeneous geospatial databases, retrievals of objects based on shape and visual characteristics, analysis of multiobject relationships for the retrieval of objects in specific spatial configurations, and semantic models to link low-level image features with high-level visual de- scriptors. GeoIRIS brings this diverse set of technologies together into a coherent system with an aim of allowing image analysts to more rapidly identify relevant imagery. GeoIRIS is able to answer analysts’ questions in seconds, such as “given a query image, show me database satellite images that have similar objects and spatial relationship that are within a certain radius of a landmark.”
@article{Shyu:GeoIRIS-2007,
author = "C. R. Shyu and M. Klaric and G. J. Scott and A. S. Barb and C. H. Davis and K. Palaniappan",
title = "GeoIRIS: Geospatial information retrieval and indexing system -- Content mining, semantics, modeling, and complex queries",
year = 2007,
journal = "IEEE Trans. Geoscience Remote Sensing",
booktitle = "Special issue on Image Information Mining for Earth Observation Data",
volume = 45,
number = 4,
pages = "839--852",
month = "Apr",
keywords = "gis, data mining, features, machine learning, parallelization, cbir",
doi = "10.1109/TGRS.2006.890579"
}
C. R. Shyu, M. Klaric, G. J. Scott, A. S. Barb, C. H. Davis, and K. Palaniappan. GeoIRIS: Geospatial information retrieval and indexing system -- Content mining, semantics, modeling, and complex queries. IEEE Trans. Geoscience Remote Sensing, Special issue on Image Information Mining for Earth Observation Data, volume 45, issue 4, pages 839--852, April 2007.