| Title |
Design of Face Recognition System Based on Pose Estimation : Comparative Studies of Pose Estimation Algorithms |
| Authors |
김진율(Kim, Jin-Yul) ; 김종범(Kim, Jong-Bum) ; 오성권(Oh, Sung-Kwun) |
| DOI |
https://doi.org/10.5370/KIEE.2017.66.4.672 |
| Keywords |
포즈 추정 Learning vector quantiztion ; K-nearest neighbor ; Radial basis function neural network |
| Abstract |
This paper is concerned with the design methodology of face recognition system based on pose estimation. In 2-dimensional face recognition, the variations of facial pose cause the deterioration of recognition performance because object recognition is carried out by using brightness of each pixel on image. To alleviate such problem, the proposed face recognition system deals with Learning Vector Quantizatioin(LVQ) or K-Nearest Neighbor(K-NN) to estimate facial pose on image and then the images obtained from LVQ or K-NN are used as the inputs of networks such as Convolution Neural Networks(CNNs) and Radial Basis Function Neural Networks(RBFNNs). The effectiveness and efficiency of the post estimation using LVQ and K-NN as well as face recognition rate using CNNs and RBFNNs are discussed through experiments carried out by using ICPR and CMU PIE databases. |