TY - GEN
T1 - Extended hierarchical gaussianization for scene classification
AU - Xu, Minqiang
AU - Zhou, Xi
AU - Li, Zhen
AU - Dai, Beiqian
AU - Huang, Thomas S.
PY - 2010
Y1 - 2010
N2 - In this paper, we propose a novel image representation for scene classification. Firstly, we model multiple order statistics of image patches via Gaussian Mixture Model(GMM) in a Bayesian framework. Secondly, we combine the information of mean and covariance of the GMM and represent it as a mean-covariance supervector through a new distance metric. Experimental results demonstrate that our new representation, by just using nearest centroid classifier, has significantly outperformed all existing methods on the fifteen scene category database.
AB - In this paper, we propose a novel image representation for scene classification. Firstly, we model multiple order statistics of image patches via Gaussian Mixture Model(GMM) in a Bayesian framework. Secondly, we combine the information of mean and covariance of the GMM and represent it as a mean-covariance supervector through a new distance metric. Experimental results demonstrate that our new representation, by just using nearest centroid classifier, has significantly outperformed all existing methods on the fifteen scene category database.
KW - Extended hierarchical gaussianization
KW - Scene classification
KW - Supervector
UR - http://www.scopus.com/inward/record.url?scp=78651080153&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=78651080153&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2010.5653825
DO - 10.1109/ICIP.2010.5653825
M3 - Conference contribution
AN - SCOPUS:78651080153
SN - 9781424479948
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 1837
EP - 1840
BT - 2010 IEEE International Conference on Image Processing, ICIP 2010 - Proceedings
T2 - 2010 17th IEEE International Conference on Image Processing, ICIP 2010
Y2 - 26 September 2010 through 29 September 2010
ER -