• Journal of the Optical Society of Korea
• /
• 제20권2호
• /
• pp.239-244
• /
• 2016

Mugshot face images, routinely collected by police, usually contain both frontal and profile views. Existing automated face recognition methods exploited mugshot databases by enlarging the gallery with synthetic multi-view face images generated from the mugshot face images. This paper, instead, proposes to match the query arbitrary view face image directly to the enrolled frontal and profile face images. During matching, the 3D face shape model reconstructed from the mugshot face images is used to establish corresponding semantic parts between query and gallery face images, based on which comparison is done. The final recognition result is obtained by fusing the matching results with frontal and profile face images. Compared with previous methods, the proposed method better utilizes mugshot databases without using synthetic face images that may have artifacts. Its effectiveness has been demonstrated on the Color FERET and CMU PIE databases.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제13권11호
• /
• pp.5546-5559
• /
• 2019

Facial action units (AUs) have recently drawn increased attention because they can be used to recognize facial expressions. A variety of methods have been designed for frontal-view AU detection, but few have been able to handle multi-view face images. In this paper we propose a method for multi-view facial AU detection using a fused multilayer, multi-task, and multi-label deep learning network. The network can complete two tasks: AU detection and facial view detection. AU detection is a multi-label problem and facial view detection is a single-label problem. A residual network and multilayer fusion are applied to obtain more representative features. Our method is effective and performs well. The F1 score on FERA 2017 is 13.1% higher than the baseline. The facial view recognition accuracy is 0.991. This shows that our multi-task, multi-label model could achieve good performance on the two tasks.

• Journal of Korean Neurosurgical Society
• /
• 제43권4호
• /
• pp.198-200
• /
• 2008

Giant cavernous malformations (GCMs) occur very rarely and little has been reported about their clinical characteristics. The authors present a case of a 20-year-old woman with a GCM. She was referred due to two episodes of generalized seizure. Computed tomography and magnetic resonance image demonstrated a heterogeneous multi-cystic lesion of $7\times5\times5$ cm size in the left frontal lobe and basal ganglia, and enhancing vascular structure abutting medial portion of the mass. These fingings suggested a diagnosis of GCM accompanying venous angioma. After left frontal craniotomy, transcortical approach was done. Total removal was accomplished and the postoperative course was uneventful. GCMs do not seem differ clinically, surgically or histopathologically from small cavernous angiomas, but imaging appearance of GCMs may be variable. The clinical, radiological feature and management of GCMs are described based on pertinent literature review.

• 한국항공우주학회지
• /
• 제50권12호
• /
• pp.889-898
• /
• 2022

본 논문에서는 3차원 전자기장의 병렬 해석 기법을 제안하였다. 시간 조화 벡터 파동 방정식 및 유한요소 기법에 기반한 전자기장 산란 해석이 수행되었으며, 모서리 기반 요소 및 2차 흡수 경계 조건이 도입되었다. 개발한 알고리즘은 유한요소망을 분할한 뒤 각 프로세서에 할당함으로써 요소별 수치적분 및 행렬 조립 과정의 병렬화를 달성하였다. 이때 부영역 생성을 위해 그래프 분할 라이브러리인 METIS가 도입되었다. 대형 희박행렬 방정식의 계산은 다중 프론탈 기법 기반 병렬 연산 라이브러리인 MUMPS를 통해 수행되었다. 개발된 프로그램의 정확도는 Mie 이론해 및 ANSYS HFSS 결과와의 비교를 통해 검증되었다. 또한 사용된 프로세서 수에 따른 가속 지표를 측정하여 확장성을 확인하였다. 완전 전기 도체 구, 등·이방성 유전체 구 및 유도탄 예제 형상에 대한 전자기장 산란 해석이 수행되었다. 개발된 프로그램의 알고리즘은 추후 유한요소 분할 및 합성법에 활용될 예정이며, 더욱 확장된 병렬 연산 성능을 목표하고자 한다.

• 대한용접접합학회:학술대회논문집
• /
• 대한용접접합학회 2003년도 추계학술발표대회 개요집
• /
• pp.156-158
• /
• 2003

An implicit finite element implementation for Leblond's transformation plasticity constitutive equations, which are widely used in welded steel structure is proposed in the framework of parallel computing. The implementation is based upon the multiplicative decomposition of deformation gradient and hyper elastic formulation. We examine the efficiency of parallel computation for the finite element analysis of a welded structure using domain-wise multi-frontal solver.

• 대한용접접합학회:학술대회논문집
• /
• 대한용접접합학회 2004년도 춘계 학술발표대회 개요집
• /
• pp.273-275
• /
• 2004

A parallel multi-frontal solver is developed for finite element analysis of an arc-welding process, which entails phase evolution, heat transfer, and deformations of structure. We verify the code via comparison to a commercial code,SYSWELD. Attention is focused on the implementation of the parallel solver using MPI library, on the speedup by parallel computation, and on the effectiveness of the solver in welding application

• 대한용접접합학회:학술대회논문집
• /
• 대한용접접합학회 2002년도 춘계학술발표대회 개요집
• /
• pp.161-163
• /
• 2002

An implicit finite element implementation for Leblond's transformation plasticity constitutive equations, which are widely used in welded steel structure is proposed in the framework of parallel computing. The implementation is based upon the updated Lagrangian formulation. We examine the efficiency of parallel compuatation for the finite element analysis of a welded structure using multi-frontal solver.

• 감성과학
• /
• 제16권4호
• /
• pp.527-534
• /
• 2013

본 연구에서는 코히어런스 분석을 통하여 시각집중 기간 동안 시간 변화에 대한 뇌기능과 관련된 공간-주파수간 연관관계를 해석하였다. 집중관련 시각자극 실험 데이터를 통해 ${\theta}$와 ${\alpha}$ 대역에서 서로 다른 두피 위치간 위상연관변화를 확인하였다. 좌우 전두엽, 전두엽과 두정엽 간 뇌유발전위는 P100, N200지점에서 위상동조를 보였으며, 전두엽과 후두엽 간 뇌유발전위는 시각 처리 정보가 반영되는 P300지점에서 위상동조를 보였다. 고정된 길이의 창을 이용하는 단구간 푸리에 변환에 비하여 연속 웨이블릿 변환은 모 웨이블릿의 파라미터 조정을 통한 다중해상도 분석이 가능하였다. 따라서 연속 웨이블릿 변환을 이용한 코히어런스 결과가 시간변화에 대한 뇌유발전위의 공간-주파수간 연관관계의 변화를 확인하는데 유효함을 확인하였다. 비 집중 자극수행에 대해서는 위상동조 현상이 나타나지 않았다.

• Journal of Information Processing Systems
• /
• 제9권1호
• /
• pp.173-188
• /
• 2013

In Facial Expression Recognition Systems (FERS), only particular regions of the face are utilized for discrimination. The areas of the eyes, eyebrows, nose, and mouth are the most important features in any FERS. Applying facial features descriptors such as the local binary pattern (LBP) on such areas results in an effective and efficient FERS. In this paper, we propose an automatic facial expression recognition system. Unlike other systems, it detects and extracts the informative and discriminant regions of the face (i.e., eyes, nose, and mouth areas) using Haar-feature based cascade classifiers and these region-based features are stored into separate image files as a preprocessing step. Then, LBP is applied to these image files for facial texture representation and a feature-vector per subject is obtained by concatenating the resulting LBP histograms of the decomposed region-based features. The one-vs.-rest SVM, which is a popular multi-classification method, is employed with the Radial Basis Function (RBF) for facial expression classification. Experimental results show that this approach yields good performance for both frontal and near-frontal facial images in terms of accuracy and time complexity. Cohn-Kanade and JAFFE, which are benchmark facial expression datasets, are used to evaluate this approach.

• 대한의용생체공학회:의공학회지
• /
• 제29권1호
• /
• pp.17-24
• /
• 2008

The aim of this paper is to report our preliminary results of investigating the spatial focalization of Zen-meditation EEG (electroencephalograph) in alpha band (8-13 Hz). For comparison, the study involved two groups of subjects, practitioners (experimental group) and non-practitioners (control group). To extract EEG alpha rhythm, wavelet analysis was applied to multi-channel EEG signals. Normalized alpha-power vectors were then constructed from spatial distribution of alpha powers, that were classified by Fuzzy C-means based algorithm to explore various brain spatial characteristics during meditation (or, at rest). Optimal number of clusters was determined by correlation coefficients of the membership-value vectors of each cluster center. Our results show that, in the experimental group, the incidence of frontal alpha activity varied in accordance with the meditation stage. The results demonstrated three different spatiotemporal modules consisting with three distinctive meditation stages normally recognized by meditation practitioners. The frontal alpha activity in two groups decreased in different ways. Particularly, monotonic decline was observed in the control group, and the experimental group showed increasing results. The phenomenon might imply various mechanisms employed by meditation and relaxation in modulating parietal alpha.