Face recognition using margin-enhanced classifier in graph-based space

Ju Chin Chen, Shang You Shi, James Jenn-Jier Lien

研究成果: Conference contribution

摘要

In this paper, we develop a face recognition system with the derived subspace learning method, i.e. classifier-concerning subspace, where not only the discriminant structure of data can be preserved but also the classification ability can be explicitly considered by introducing the Mahalanobis distance metric in the subspace. Most of graph-based subspace learning methods find a subspace with the preservation of certain geometric and discriminant structure of data but not explicitly include the classification information from the classifier. Via the distance metric, which is constrained by k-NN classification rule, the pairwise distance relation can be locally adjusted and thus the projected data in the classifier-concerning subspace are more suitable for k-NN classifier. In addition, an iterative procedure is derived to get rid of the overfitting problem. Experimental results show that the proposed system can yield the promising recognition results under various lighting, pose and expression conditions.

原文English
主出版物標題VISAPP 2010 - Proceedings of the International Conference on Computer Vision Theory and Applications
頁面382-388
頁數7
出版狀態Published - 2010 九月 10
事件5th International Conference on Computer Vision Theory and Applications, VISAPP 2010 - Angers, France
持續時間: 2010 五月 172010 五月 21

出版系列

名字VISAPP 2010 - Proceedings of the International Conference on Computer Vision Theory and Applications
2

Other

Other5th International Conference on Computer Vision Theory and Applications, VISAPP 2010
國家France
城市Angers
期間10-05-1710-05-21

All Science Journal Classification (ASJC) codes

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

指紋 深入研究「Face recognition using margin-enhanced classifier in graph-based space」主題。共同形成了獨特的指紋。

引用此