课题组获得2项中国石油大学（华东）自主创新科研项目

学院消息，课题组获得2项中国石油大学（华东）自主创新科研项目，其中1项青年基金（负责人刘伟锋），研究生创新基金1项（负责人姜英）。

TEST

This is a test post!

A co-authored paper has been accepted by TMM

A co-authored paper has been accepted by TMM.  In this paper, we presented a manifold based SVM for cloud computing.

One paper is accepted by CIAC2013

Efficient Discriminative K-SVD for Facial Expression Recognition

Weifeng Liu, Caifeng Song and Yanjiang Wang

Dictionary learning has attracted growing intention for its prominent performance in many computer vision applications including facial expression recognition (FER). Discriminative K-SVD (D-KSVD) is one of conventional dic-tionary learning methods, which can effectively unify dictionary learning and classifier. However, the computation is huge when applying D-KSVD directly on Gabor features which has a high dimension. To tackle this problem, in this paper, we employ random projection on Gabor features and then put the reduced features into D-KSVD schema to obtain sparse representation and dictionary. To evaluate the performance, we implement the proposed method for FER on JAFFE database. We also employ support vector machine (SVM) on the sparse codes for FER. Ex-perimental results demonstrate that the computation is reduced a lot with little per-formance lost.