计算机科学 ›› 2014, Vol. 41 ›› Issue (1): 311-.

• 图形图像与模式识别 • 上一篇    

一种快速的判别公共向量分类方法

韩姗姗,黄凯,王万良,郑建炜,蒋一波   

  1. 浙江工业大学计算机科学与技术学院 杭州310023;浙江工业大学计算机科学与技术学院 杭州310023;浙江工业大学计算机科学与技术学院 杭州310023;浙江工业大学计算机科学与技术学院 杭州310023;浙江工业大学计算机科学与技术学院 杭州310023
  • 出版日期:2018-11-14 发布日期:2018-11-14
  • 基金资助:
    本文受国家自然科学基金(61070043),浙江省自然科学基金(LY12F02033,LQ12F03011)资助

Faster Discriminative Common Vectors Classification Approach

HAN Shan-shan,HUANG Kai,WANG Wan-liang,ZHENG Jian-wei and JIANG Yi-bo   

  • Online:2018-11-14 Published:2018-11-14

摘要: 在传统DCV的基础上,提出了一种改进的快速DCV分类方法。该方法与传统的DCV分类方法相比,在保证识别率相同的情况下具有较快的分类速率。传统的DCV分类方法通过计算特征向量之间的距离来进行分类,而所提快速DCV分类方法则通过标量计算完成分类。理论分析及复杂度计算表明,快速DCV分类方法的分类速率是传统DCV分类方法的2倍左右,在Yale、ORL和PIE 3种人脸数据库得到的对比仿真实验结果验证了该算法的有效性。

关键词: 判别公共向量,快速分类算法,人脸识别

Abstract: This paper proposed an improved Fast Discriminative Common Vectors (FDCV) classification algorithm based on the traditional Discriminative Common Vectors (DCV).Compared with the traditional DCV,the FDCV not only has a faster classification rate,but also guarantees the same recognition performance.The FDCV does the classification by calculating the distance between scalars but not vectors which are used in the traditional DCV.Theoretical ana-lysis and complexity calculation show that Faster DCV has twice the classifying speed of the traditional DCV.The simulation experiment on the three face databases of Yale Face Database B,ORL Database and PIE Database further verifies the effectiveness of the algorithm.

Key words: Discriminative common vectors,Fast classification algorithm,Face recognition

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