Document Detail


Image transform bootstrapping and its applications to semantic scene classification.
MedLine Citation:
PMID:  15971924     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The performance of an exemplar-based scene classification system depends largely on the size and quality of its set of training exemplars, which can be limited in practice. In addition, in nontrivial data sets, variations in scene content as well as distracting regions may exist in many testing images to prohibit good matches with the exemplars. Various boosting schemes have been proposed in machine learning, focusing on the feature space. We introduce the novel concept of image-transform bootstrapping using transforms in the image space to address such issues. In particular, three major schemes are described for exploiting this concept to augment training, testing, and both. We have successfully applied it to three applications of increasing difficulty: sunset detection, outdoor scene classification, and automatic image orientation detection. It is shown that appropriate transforms and meta-classification methods can be selected to boost performance according to the domain of the problem and the features/classifier used.
Authors:
Jiebo Luo; Matthew Boutell; Robert T Gray; Christopher Brown
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Publication Detail:
Type:  Comparative Study; Evaluation Studies; Letter    
Journal Detail:
Title:  IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society     Volume:  35     ISSN:  1083-4419     ISO Abbreviation:  IEEE Trans Syst Man Cybern B Cybern     Publication Date:  2005 Jun 
Date Detail:
Created Date:  2005-06-23     Completed Date:  2005-07-19     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  9890044     Medline TA:  IEEE Trans Syst Man Cybern B Cybern     Country:  United States    
Other Details:
Languages:  eng     Pagination:  563-70     Citation Subset:  IM    
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Artificial Intelligence*
Cluster Analysis
Computer Graphics
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Information Storage and Retrieval / methods*
Numerical Analysis, Computer-Assisted
Pattern Recognition, Automated / methods*
Semantics
Signal Processing, Computer-Assisted

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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