Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.authorXiao, Yangen
dc.contributor.authorWu, Jianxinen
dc.contributor.authorYuan, Junsongen
dc.identifier.citationXiao, Y., Wu, J., & Yuan, J. (2014). mCENTRIST: A Multi-Channel Feature Generation Mechanism for Scene Categorization. IEEE Transactions on Image Processing, 23(2), 823-836.en
dc.description.abstractmCENTRIST, a new multi-channel feature generation mechanism for recognizing scene categories, is proposed in this paper. mCENTRIST explicitly captures the image properties that are encoded jointly by two image channels, which is different from popular multi-channel descriptors. In order to avoid the curse of dimensionality, tradeoffs at both feature and channel levels have been executed to make mCENTRIST computationally practical. As a result, mCENTRIST is both efficient and easy to implement. In addition, a hyper opponent color space is proposed by embedding Sobel information into the opponent color space for further performance improvements. Experiments show that mCENTRIST outperforms established multi-channel descriptors on four RGB and RGB-NIR datasets, including aerial orthoimagery, indoor and outdoor scene category recognition tasks. Experiments also verify that the hyper opponent color space enhances descriptors’ performance effectively.en
dc.format.extent14 p.en
dc.relation.ispartofseriesIEEE transactions on image processingen
dc.rights© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [].en
dc.subjectDRNTU::Engineering::Electrical and electronic engineeringen
dc.titlemCENTRIST : a multi-channel feature generationen
dc.typeJournal Articleen
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.description.versionAccepted versionen
item.fulltextWith Fulltext-
Appears in Collections:EEE Journal Articles
Files in This Item:
File Description SizeFormat 
mCENTRIST-A Multi-channel Feature Generation.pdf3.36 MBAdobe PDFThumbnail

Citations 5

Updated on Mar 3, 2021

Citations 5

Updated on Mar 2, 2021

Page view(s) 50

Updated on Apr 22, 2021

Download(s) 10

Updated on Apr 22, 2021

Google ScholarTM




Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.