@article {140,
	title = {Discriminant parallel feature fusion based on maximum margin criterion for pattern classification},
	journal = {Journal of Digital Information Management},
	volume = {6},
	year = {2008},
	note = {Cited By (since 1996):1Export Date: 10 July 2014},
	month = {2008},
	pages = {203 - 207},
	abstract = {In this paper, we propose a novel parallel feature fusion based maximum margin criterion, namely discriminant parallel feature fusion, for pattern classification. The advantage of algorithm lies in: 1) A constrained optimization problem based on maximum margin criterion is created to solve the optimal fusion coefficients, which causes that fused data has the largest class discriminant in the fused feature space. 2) An unique solution of optimization problem is transformed to an eigenvalue problem, which causes the proposed fusion strategy to perform a consistent performance. Besides of the detailed theory derivation, many experimental evaluations also are presented in this paper.},
	keywords = {Discriminant parallel feature fusion, Maximum margin criterion, Parallel feature fusion},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-72449120326\&partnerID=40\&md5=45d5e7fee23074133279fb977574a551},
	author = {Li, J.-B. and Chu, S.-C. and Pan, J.-S.}
}
@article {149,
	title = {Information hiding and multimedia signal processing},
	journal = {Journal of Digital Information Management},
	volume = {6},
	year = {2008},
	note = {Export Date: 10 July 2014},
	month = {2008},
	pages = {140 - 142},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-72449205976\&partnerID=40\&md5=cf60ca8c2c2cff6aee125963a9d4800c},
	author = {Pan, J.-S. and Abraham, A.}
}
@article {85,
	title = {Rotation-based three dimensional shape descriptor},
	journal = {Journal of Digital Information Management},
	volume = {5},
	year = {2007},
	note = {Export Date: 10 July 2014},
	month = {2007},
	pages = {138 - 141},
	abstract = {Recent developments in techniques for modeling, digitizing and visualizing three dimensional shapes have led to an explosion in the number of available three dimensional models on the Internet and in many domain-specific databases. However, how to describe three dimensional shapes is a difficult problem. A new three dimensional shape description method based on rotation is proposed in this paper. The first step is to sample points on the surface and compute normal vectors. Secondly, we do Gauss mapping and rotate model, at the same time, rotate the Gauss sphere. The third step is to analysis normal distributions on the sphere surface. Then the Euclidean distance is computed, and finally a statistic histogram is constructed. Experimental results show the effectiveness of this method.},
	keywords = {3 d space descriptors, Gauss mapping, Three dimensional shapes},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-70350689502\&partnerID=40\&md5=11b5b46b07b7146eba309aa78ff8f501},
	author = {Luo, H. and Chu, S.-C. and Pan, J.-S. and Lu, Z.-M.}
}
