基于Fisher核的混合核构造研究

摘要

为了解决传统的由混合核组成的核函数的参数选择时,由于参数过多导致参数选择时间过长的问题,提出了一种基于Fisher核构造混合核的方法.利用Fisher核的无参特性,可以减少混合核的参数个数,从而有效减少了参数选择的时间.在典型彩色人脸库上的实验结果显示,与传统的混合核相比,基于Fisher核的混合核的参数选择时间明显减少且识别正确率有所提高,表明了所提出方法的有效性.%To address the too much time consumption issue in the selection of parameter values existing in the mixed kernel composed of traditional kernels, a method of constructing mixed kernel based on Fisher-kernel was proposed. Because of the non-parameter characteristic of Fisher-kernel, the number of parameters in the Fisher-kernel based mixed kernel was effectively reduced, thus the selection time of parameter values was also effectively reduced. The experimental results on typical color face databases show that, compared with traditional mixed kernel, the parameter selection time of Fisher-kernel based mixed kernel is significantly reduced and the correctness rate of recognition is improved, which confirms the effectiveness of the proposed method.