Multi-index, multi-object content-based retrieval with spatial summarization
No Thumbnail Available
Authors
Meeting name
Sponsors
Date
Journal Title
Format
Thesis
Abstract
In recent years we have seen the development of several novel content-based retrieval (CBR) systems that have had success by focusing on a specific domain and exploiting domain-speci c information. CBR systems allow users to query a media database using item content as opposed submitting a text-based query. In many CBR applications, the input to the search process is a complicated object that may be composed of several constituent parts. The proposed approach performs CBR queries by decomposing a complex query into several heterogeneous queries. We have developed a multi-index, multi-object CBR framework for geospatial imagery retrieval that extracts features specifically developed for high-resolution commercial satellite imagery. The results of these queries will be spatially summarized for a user based on both retrieval score and spatial distance. This allows results to be presented in a logical manner to allow for more efficient interpretation by the user. Further, we propose to develop an additional search capability that allows for multi-object searches by spatial configuration rather than simply by object-to-object correspondence. Additionally, to confront situations where a user has determined that certain search results are not relevant, we will provide online and memory-based relevance feedback algorithms for use with multi-index, multi-object CBR systems. The experimental results demonstrate the efficiency and accuracy of the proposed methods; moreover, through the fusion of multi-index and multi-object search techniques, we are able to construct new, sophisticated query mechanisms.
Table of Contents
DOI
PubMed ID
Degree
Ph. D.
Thesis Department
Rights
OpenAccess.
License
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 License.