摘要： 引入空间变换的思想,提出了一种基于空间变换的核Fisher鉴别分析,与KFDA不同的是,该方法只需在一个较低维的空间内执行,从而较大幅度地降低了求解最优鉴别矢量集的计算量,提高了计算速度。在ORL标准人脸库上的试验结果验证了所提方法的有效性。

关键词: 空间变换, 核Fisher鉴别分析, 特征抽取, 人脸识别

Abstract: Considering the above weaknesses, based on the idea of space transformation, a fast algorithm for extraction of the optimal nonlinear discriminant vectors in high dimensional feature space is presented. Unlike the kernel fisher discriminant analysis (KFDA) method, the proposed algorithm only need to perform in a low dimensional transformed space, which leads to significant computational reduction. The experimental results on ORL face database verify that the presented approach is faster than KFDA in terms of recognition time while retain their accuracy.

中图分类号: 

• TP391.4