Image Sense Disambiguation in Web Image Retrieval
Date Issued
2008
Date
2008
Author(s)
Chang, Yih-Cheng
Abstract
In these few years, images in the web have explosively increased. Image retrieval for web images becomes more and more important. Image sense disambiguation/discrimination (ISD) is a task to disambiguate/discriminate image senses of retrieved web images. This technology can be used to improve the performance of web image retrieval or be applied in image annotation or object recognition tasks to help collecting training samples. ISD is a new task not being well studied but may become important in the future.n this thesis, we analyze and discuss ISD problem. We propose a method to find senses of web images. There may be many senses in the web are not be included in the dictionary. For each sense, we collect sample images and pages without human annotation. Unlike previous approaches that use clustering methods in ISD, we use classifying method instead. Four kinds of classifiers and a merge method are proposed in this thesis. The steps of our methods are evaluated and discussed and in the end of this thesis we will summarize our work and discuss some interesting future works.
Subjects
image sense disambiguation
image sense discrimination
web image retrieval
image annotation
object recognition
Type
thesis
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