• 한국멀티미디어학회논문지
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• 제14권4호
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• pp.494-503
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• 2011

본 논문에서는 스마트폰에서 웃음 치료를 위한 표정인식 애플리케이션을 제안한다. 제안된 방법에서는 스마트폰의 전면 카메라 영상으로부터 AdaBoost 얼굴 검출 알고리즘을 이용하여 얼굴을 검출한다. 얼굴을 검출한 다음에는 얼굴 영상으로부터 입술 영역을 검출한다. 그 다음 프레임부터는 얼굴을 검출하지 않고 이전 프레임에서 검출된 입술영역을 3단계 블록 매칭 기법을 이용하여 추적한다. 카메라와 얼굴 사이의 거리에 따라 입술 영역의 크기가 달라지므로, 입술 영역을 구한 다음에는 고정된 크기로 정규화한다. 그리고 주변 조명 상태에 따라 영상이 달라지므로, 본 논문에서는 히스토그램 매칭과 좌우대칭을 결합하는 조명 정규화 알고리즘을 이용하여 조명 보정 전처리를 함으로써 조명에 의한 영향을 줄일 수 있도록 하였다. 그 다음에는 검출된 입술 영상에 주성분 분석을 적용하여 특징 벡터를 추출하고 다층퍼셉트론 인공신경망을 이용하여 실시간으로 웃음 표정을 인식한다. 스마트폰을 이용하여 실험한 결과, 제안된 방법은 초당 16.7프레임을 처리할 수 있어서 실시간으로 동작 가능하였고 인식률 실험에서도 기존의 조명 정규화 방법보다 개선된 성능을 보였다.

• 대한전자공학회논문지
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• 제25권5호
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• pp.501-508
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• 1988

This paper presents the light-induced effects on the elelctrical and optical properties of undoped and doped hydrogenated amorphous silicon films. The changes in the conductivities and the activation energies of various types of a-Si:H films due to the prolonged exposure to light have been characterized as a function of deposition conditions and illumination periods. The dark conductivity changes may be quenched for heavier doped a-Si:H films. We have also analyzed the variations of micro-structure of a-Si:H film such as silicon-hydrogen bondings in the rocking and stretching modes utilizing infrared spectroscopy. From the experimental results, it is elucidated that doping effects must be crucial to the degradations of the fundamental properties of a-Si:H due to light-induced effects.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권2호
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• pp.763-774
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• 2015

Hand posture recognition has been a wide region of applications in Human Computer Interaction and Computer Vision for many years. The problem arises mainly due to the high dexterity of hand and self-occlusions created in the limited view of the camera or illumination variations. To remedy these problems, a hand posture recognition method using 3-D point cloud is proposed to explicitly utilize 3-D information from depth maps in this paper. Firstly, hand region is segmented by a set of depth threshold. Next, hand image normalization will be performed to ensure that the extracted feature descriptors are scale and rotation invariant. By robustly coding and pooling 3-D facets, the proposed descriptor can effectively represent the various hand postures. After that, SVM with Gaussian kernel function is used to address the issue of posture recognition. Experimental results based on posture dataset captured by Kinect sensor (from 1 to 10) demonstrate the effectiveness of the proposed approach and the average recognition rate of our method is over 96%.

• 한국실내디자인학회논문집
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• 제24권4호
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• pp.91-98
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• 2015

Double skin façade is known that several features affected the building energy and daylighting performance. That is why the envelope is able to consist of all architectural materials such as glass, aluminum, wood and insulation for vision of residents and workers in buildings. Its specifications is very diverse according to the building designers and building owners. In recent times, visual environment became a major focus and resulted in the development of cutting edge engineering of diverse glazing systems and shading devices by growing interests of friendly environment. Thus this research has evaluated the fluctuations of interior lighting and atmospheric conditions based on double skin facade systems. Especially in terms of daylighting environment as dependent on solar variations, this research provides quantitative analysis of interior lighting conditions and how it affects the living conditions as well as improve the design of interior spaces.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.605-608
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• 1996

The aim of this thesis is to develop a SMT-components placement inspection system equipped with a visual sensor. The visual sensor, which consists of a camera and 2-layer LED illuminator, developed to inspect the component placement state such as missing, shift, flipping, polarity and tomb-stone. on PCB in the reflow-process. In practical applications, however, it is too hard to classify component from images mixed pad on PCB, cream solder paste and component. To overcome the problem, this thesis proposes the 2-layer illumination method and the heuristic image processing algorithms according to inspection type. To show the effectiveness of the proposed approach, a series of experiments on the inspection were conducted. The results show that the proposed method is robust to visual noise and variations in component conditions.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.957-958
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• 2008

The human facial appearances vary globally and locally according to identity, pose, illumination, and expression variations. In this paper, we propose a hybrid-nonsmooth nonnegative matrix factorization (hybrid-nsNMF) based appearance model to represent various facial appearances which vary globally and locally. Instead of using single smooth matrix in nsNMF, we used two different smooth matrixes and combine them to extract global and local basis at the same time.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.138.3-138
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• 2001

Because face has non-rigid structure and is influenced by illumination, we need robust face detection algorithm with the variations of external environments (orientation of lighting and face, complex background, etc.). In this paper we develop a new face detection algorithm to achieve robustness. First we transform RGB color into other color space, in which we can reduce lighting effect much. Second, hierarchical image segmentation technique is used for dividing a image into homogeneous regions. This process uses not only color information, but also spatial information. One of them is used in segmentation by histogram analysis, the other is used in segmentation by grouping. And we can select face region among the homogeneous regions by using facial features.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권6호
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• pp.2217-2229
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• 2015

Since the variations of illumination, the irregular changes of human shapes, and the partial occlusions, multiple person tracking is a challenging work in computer vision. In this paper, we propose a graph clustering method based on spatio-temporal information of moving objects for multiple person tracking. First, the part-based model is utilized to localize individual foreground regions in each frame. Then, we heuristically leverage the spatio-temporal constraints to generate a set of reliable tracklets. Finally, the graph shift method is applied to handle tracklet association problem and consequently generate the completed trajectory for individual object. The extensive comparison experiments demonstrate the superiority of the proposed method.

• 전자공학회논문지D
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• 제34D권7호
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• pp.45-55
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• 1997

Electircal characteristics of HgCdTe photodiodes with a heterostructure to achieve high performance are analyzed numerically. A two-dimensional device simulator which can handle a HgCdTe heterostructure, was developed for this work. The effects of band nonparabolicity, carrier degeneracy, and band-offset of heterointerace are included in a carrier transport model. A unified generation-recombination model includes simultaneously phonon-assisted tunneling and pure tunneling of carriers via traps is newly employed for describing the electric field and temperature dependency of dark current effectively. Furthermore, to accurately predict the effect mole fraction variations on genration rates, ray-trace algorithm is incorporated in the our simulator. Under the various circumstances such as dark, illumination, and surface states, electrical properties of planar heterostructure photodiode are presented and those of homojunction are compared. These results serve as a explanation of cap layer's role on performance.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.170-178
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• 2017

Biometric recognition is one of the major challenging topics which needs high performance of recognition accuracy. Most of existing methods rely on a single source of biometric to achieve recognition. The recognition accuracy in biometrics is affected by the variability of effects, including illumination and appearance variations. In this paper, we propose a new multimodal biometrics recognition using convolutional neural network. We focus on multimodal biometrics from face and periocular regions. Through experiments, we have demonstrated that facial multimodal biometrics features deep learning framework is helpful for achieving high recognition performance.