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Article: Scene categorization with multiscale category-specific visual words

TitleScene categorization with multiscale category-specific visual words
Authors
KeywordsCategory-Specific
Multiscale
Scene Categorization
Visual Words
Issue Date2009
PublisherSPIE - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oe
Citation
Optical Engineering, 2009, v. 48 n. 4, article no. 047203 How to Cite?
AbstractWe propose a novel scene categorization method based on multiscale category-specific visual words. The novelty of the proposed method lies In two aspects: (1) visual words are quantized In a multiscale manner that combines the global-feature-based and local-feature-based scene categorization approaches into a uniform framework; (2) unlike traditional visual word creation methods, which quantize visual words from the entire set of training, we form visual words from the training images grouped in different categories and then collate visual words from different categories to form the final codebook. This generation strategy Is capable of enhancing the discriminative ability of the visual words, which is useful for achieving better classification performance. The proposed method is evaluated over two scene classification data sets with 8 and 13 scene categories, respectively. The experimental results show that the classification performance is significantly improved by using the multiscale category-specific visual words over that achieved by using the traditional visual words. Moreover, the proposed method Is comparable with the best methods reported in previous literature in terms of classification accuracy rate (88.81% and 85.05% accuracy rates for data sets 1 and 2, respectively) and has the advantage in simplicity. © 2009 Society of Photo Optical Instrumentation Engineers.
Persistent Identifierhttp://hdl.handle.net/10722/155515
ISSN
2023 Impact Factor: 1.1
2023 SCImago Journal Rankings: 0.331
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorQin, Jen_US
dc.contributor.authorYung, NHCen_US
dc.date.accessioned2012-08-08T08:33:53Z-
dc.date.available2012-08-08T08:33:53Z-
dc.date.issued2009en_US
dc.identifier.citationOptical Engineering, 2009, v. 48 n. 4, article no. 047203en_US
dc.identifier.issn0091-3286en_US
dc.identifier.urihttp://hdl.handle.net/10722/155515-
dc.description.abstractWe propose a novel scene categorization method based on multiscale category-specific visual words. The novelty of the proposed method lies In two aspects: (1) visual words are quantized In a multiscale manner that combines the global-feature-based and local-feature-based scene categorization approaches into a uniform framework; (2) unlike traditional visual word creation methods, which quantize visual words from the entire set of training, we form visual words from the training images grouped in different categories and then collate visual words from different categories to form the final codebook. This generation strategy Is capable of enhancing the discriminative ability of the visual words, which is useful for achieving better classification performance. The proposed method is evaluated over two scene classification data sets with 8 and 13 scene categories, respectively. The experimental results show that the classification performance is significantly improved by using the multiscale category-specific visual words over that achieved by using the traditional visual words. Moreover, the proposed method Is comparable with the best methods reported in previous literature in terms of classification accuracy rate (88.81% and 85.05% accuracy rates for data sets 1 and 2, respectively) and has the advantage in simplicity. © 2009 Society of Photo Optical Instrumentation Engineers.en_US
dc.languageengen_US
dc.publisherSPIE - International Society for Optical Engineering. The Journal's web site is located at http://www.spie.org/oeen_US
dc.relation.ispartofOptical Engineeringen_US
dc.rightsCopyright 2009 Society of Photo‑Optical Instrumentation Engineers (SPIE). One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this publication for a fee or for commercial purposes, and modification of the contents of the publication are prohibited. This article is available online at https://doi.org/10.1117/1.3115471-
dc.subjectCategory-Specificen_US
dc.subjectMultiscaleen_US
dc.subjectScene Categorizationen_US
dc.subjectVisual Wordsen_US
dc.titleScene categorization with multiscale category-specific visual wordsen_US
dc.typeArticleen_US
dc.identifier.emailYung, NHC:nyung@eee.hku.hken_US
dc.identifier.authorityYung, NHC=rp00226en_US
dc.description.naturepublished_or_final_versionen_US
dc.identifier.doi10.1117/1.3115471en_US
dc.identifier.scopuseid_2-s2.0-64549114636en_US
dc.identifier.hkuros164691-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-64549114636&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume48en_US
dc.identifier.issue4en_US
dc.identifier.spagearticle no. 047203-
dc.identifier.epagearticle no. 047203-
dc.identifier.isiWOS:000265642200032-
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridQin, J=24450951900en_US
dc.identifier.scopusauthoridYung, NHC=7003473369en_US
dc.customcontrol.immutablejt 130409-
dc.identifier.issnl0091-3286-

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