• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.44 no.2 s.314
• /
• pp.82-92
• /
• 2007

This paper describes a novel global shape (GS) feature based on radial basis function network (RBFN) and the extraction method of the proposed feature for 3D face recognition. RBFN is the weighted sum of RBfs, it well present the non-linearity of a facial shape using the linear combination of RBFs. It is the proposed facial feature that the weights of RBFN learned by the horizontal profiles of a face. RBFN based feature expresses the locality of the facial shape even if it is GS feature, and it reduces the feature complexity like existing global methods. And it also get the smoothing effect of the facial shape. Through the experiments, we get 94.7% using the proposed feature and hidden markov model (HMM) to match the features for 100 gallery set with those for 300 test set.

• Korean Journal of Cognitive Science
• /
• v.11 no.2
• /
• pp.79-87
• /
• 2000

In this paper we present a face recognition and face detection algorithm in MPEG compressed video. The proposed method consists three stage of processing steps. The first step is to produce a spatially reduced DC image form MPEG compressed video for processing. And the second step is face detection on reduced DC image. Finally, the last step is face recognition on partially extracted compressed frames which contain the detected faces. The spatially reduced DC image is produced from two dimensional inverse DCT of the DC coefficient and the first two AC coefficients. The face detection is performed on DC image and face recognition is performed on one extracted frame per GOP by using the K-L transform. In order to evaluate the proposed method, we carried out experiments on video database. The experiment results show the proposed method is very efficient and helpful for target tasks.

• Proceedings of the Korean Information Science Society Conference
• /
• 2002.10d
• /
• pp.496-498
• /
• 2002

정보화 시대가 도래하고 급격히 발전해 감에 있어 모든 형태의 정보가 가장 중요한 가치로 평가되고있고 멀티미디어가 급속히 발달함으로 인해 산업 및 생활에서 정보 보안이 매우 중요한 관건이 되어 정보보안의 여러 형태 중의 한가지로서 얼굴인식은 최근 연구가 활발하게 이루어지고 있다. 얼굴인식은 신체의 일부를 직접 접촉하지 않으므로 사용자로 하여금 불편함이나 기계적 반감을 불러일으키지 않는 장점으로 그 비중은 커질 것으로 예상되고 있다. 영상에 있어서 많은 중요한 정보가 영상픽셀들간의 고차원적인 연관 속에 담겨져 있을 것이다. ICA(Independent Component Analysis)는 이러한 고차원적인 정보를 2차원적인 정보로부터 추출하는 것이 아니라 각각의 고차원적인 정보를 직접 얻을 수 있는 장점을 이용하고 있다. 본 논문에서는 얼굴인식시스템의 첫번째 관문인 배경화면으로부터의 얼굴영상을 구별해내는 데 있어 ICA를 적용하여 기저영상벡터공간(Source or Basis Image Space)을 구하고 그 공간에 테스트할 영상을 투영시켜 얻어진 벡터의 consine distance를 이용하여 얼굴영상을 추출하는 방법에 대해서 제안하였다.

• The Journal of the Korea Contents Association
• /
• v.9 no.6
• /
• pp.1-8
• /
• 2009

There are a lot of influences, such as location of camera, luminosity, brightness, and direction of light, which affect the performance of 2-dimensional image recognition. This paper suggests an adaptive method for face-image recognition in noisy environments using evolvable filtering and feature extraction which uses one sample image from camera. This suggested method consists of two main parts. One is the environmental-adjustment module which determines optimum sets of filters, filter parameters, and dimensions of features by using "steady state genetic algorithm". The other another part is for face recognition module which performs recognition of face-image using the previous results. In the processing, we used Gabor wavelet for extracting features in the images and k-Nearest Neighbor method for the classification. For testing of the adaptive face recognition method, we tested the adaptive method in the brightness noise, in the impulse noise and in the composite noise and verified that the adaptive method protects face recognition-rate's rapidly decrease which can be occurred generally in the noisy environments.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.19 no.5
• /
• pp.648-654
• /
• 2009

In this paper, a method called bilateral diagonal 2DLDA is proposed for face recognition. Two methods called Dia2DPCA and Dia2DLDA were suggested to reserve the correlations between the variations in the rows and columns of diagonal images. However, these methods work in the row direction of these images. A row-directional projection matrix can be obtained by calculating the between-class and within-class covariance matrices making an allowance for the column variation of alternative diagonal face images. In addition, column-directional projection matrix can be obtained by calculating the between-class and within-class covariance matrices making an allowance for the row variation in diagonal images. A bilateral projection scheme was applied using left and right multiplying projection matrices. As a result, the dimension of the feature matrix and computation time can be reduced. Experiments carried out on an ORL face database show that the proposed method with three different distance measures, namely, Frobenius, Yang and AMD, is more accurate than some methods, such as 2DPCA, B2DPCA, 2DLDA, etc.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2009.01a
• /
• pp.163-167
• /
• 2009

본 논문에서는 크게 2단계에 걸쳐 다양한 형태의 얼굴을 가진 2차원 애니메이션 상의 캐릭터 얼굴구성요소를 추출하고 표정을 분석한다. 첫 번째 단계에서는, 기존의 얼굴인식 및 표정인식 분야에서 이용되었던 동적메쉬모델을 간소화하여 캐릭터 얼굴에 적용하기 위한 최적의 표준 메쉬모델을 제작하고, 이 모델을 사용하여 얼굴구성요소의 위치 및 형태정보를 추출한다. 두 번째 단계에서는, 앞 단계에서 추출된 3가지 얼굴구성요소(눈썹, 눈, 입)를 사용하여 FACS(Facial Action Coding System)에 정의된 AU(Action Units) 44개 중 12개의 AU를 사용하여 캐릭터의 5까지 기본적인 얼굴 표정에 대해 분석 및 정의한다. 본 논문에서 정의한 AU로 기본적인 5가지 얼굴표정에 대해 표정분석 정확도를 측정하였고, 서로 다른 캐릭터에 실험함으로써 제안된 AU정의의 타당성을 제시한다.

• Journal of Advanced Navigation Technology
• /
• v.17 no.6
• /
• pp.726-735
• /
• 2013

This paper proposed face recognition methods about performance improvement of the face recognition using the properties of wavelet transform. Using discrete wavelet transform is Daubechies D4 filter that is similar to mother wavelet transform. For discrete wavelet transform method, In this case, by using LL subband only we can reduce processing time and amount of memory in recognition processing. To improve recognition ratio without further loss of 2 dimensional data changing, We applies 2D LDA. We perform SVM training algorithm to the feature vector obtained by 2D LDA. Experiment is performed using ORL database set and Yale database set by Matlab program. Test result shows that proposed method is superior to existence methods in recognition rate and performance time.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.41 no.4
• /
• pp.45-50
• /
• 2004

In this paper, we propose a new PCA-based LDA Mixture Algorithm(PLMA) for real-time face recognition system. This system greatly consists of the two parts: 1) face extraction part; 2) face recognition part. In the face extraction part we applied subtraction image, color filtering, eyes and mouth region detection, and normalization method, and in the face recognition part we used the method mixing PCA and LDA in extracted face candidate region images. The existing recognition system using only PCA showed low recognition rates, and it is hard in the recognition system using only LDA to apply LDA to the input images as it is when the number of image pixels ire small as compared with the training set. To overcome these shortcomings, we reduced dimension as we apply PCA to the normalized images, and apply LDA to the compressed images, therefore it is possible for us to do real-time recognition, and we are also capable of improving recognition rates. We have experimented using self-organized DAUface database to evaluate the performance of the proposed system. The experimental results show that the proposed method outperform PCA, LDA and ICA method within the framework of recognition accuracy.

• Journal of KIISE
• /
• v.44 no.3
• /
• pp.295-305
• /
• 2017

Facial appearance is greatly influenced by illumination conditions, and therefore illumination variation is one of the factors that degrades performance of face recognition systems. In this paper, we propose a robust method for face representation under varying illumination conditions, combining non-alpha Weberface (non-alpha WF) and histogram equalization. We propose a two-step method: (1) for a given face image, non-alpha WF, which is not applied a parameter for adjusting the intensity difference between neighboring pixels in WF, is computed; (2) histogram equalization is performed to non-alpha WF, to make a uniform histogram distribution globally and to enhance the contrast. $(2D)^2PCA$ is applied to extract low-dimensional discriminating features from the preprocessed face image. Experimental results on the extended Yale B face database and the CMU PIE face database show that the proposed method yielded better recognition rates than several illumination processing methods as well as the conventional WF, achieving average recognition rates of 93.31% and 97.25%, respectively.

• Korean Journal of Cognitive Science
• /
• v.11 no.2
• /
• pp.1-10
• /
• 2000

Realistic facial animation research field which communicates with human and computer using face has increased recently. The human face is the part of the body we use to recognize individuals and the important communication channel that understand the inner states like emotion. To provide the intelligent interface. computer facial animation looks like human in talking and expressing himself. Facial modeling and animation research is focused on realistic facial animation recently. In this article, we suggest the method of facial modeling and animation for realistic facial synthesis. We can make a 3D facial model for arbitrary face by using generic facial model. For more correct and real face, we make the Korean Generic Facial Model. We can also manipulate facial synthesis based on the physical characteristics of real facial muscle and skin. Many application will be developed such as teleconferencing, education, movies etc.