• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.478-481
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• 2008

기존 핑거 트래킹(Finger Tracking)을 수행하는데 있어 핑거팁(Finger-tip)을 구하는 방법 중 가장 일반적인 방법은 먼저 피부색 정보(Skin Color)를 추출한다. 그 다음 블럽(Blob) 함수의 블럽 컬러링(Blob Coloring) 알고리즘을 통하여 피부 윤곽선(Skin Contour)를 구하고, 그 중 가장 최상위 점을 핑거팁으로 정한다. 그러나 이 방법은 밴딩 핑거(Bending Finger) 상태에서 핑거팁 위치를 측정할 때 실제 손가락 끝이 아닌 잘못된 위치를 잡는 문제점을 가지고 있다. 본 논문에서 제안하는 방법은 밴딩 핑거 상태에서의 핑거 트래킹시 잘못된 핑거팁을 측정하는 문제점을 사용자들의 성향을 통해 미리 예상하고 보정함으로써 성능을 향상시키고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.663-664
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• 2023

코로나 19 이후 트렌드에 민감한 MZ 세대가 패션을 선도하면서 다양한 패션이 출현하여 사람들의 선택지를 확장하고 있으며 패션에 관심을 갖고 의상을 구매하는 사례가 증가함에 따라 사람들은 자신을 돋보이게 해주는 의상을 선택하는데 많은 시간을 할애한다. 본 논문에서 개인의 피부 톤, 눈색, 머리색을 분석하여 추출한 퍼스널 컬러를 기반으로 염색된 개인 맞춤 의상을 제공하는 시스템을 제안한다. 기존에 염색공정 시스템의 한계점을 해결하기 위해 딥러닝 모델을 기반으로 원단 염색을 고도화하고 개인 맞춤형 의상 제작의 새로운 제안으로 의류산업에 변화를 주고자 한다. 향후 제안한 시스템의 현실적인 검증과 성능 평가가 필요하다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.05a
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• pp.165-170
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• 2003

This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.3 s.309
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• pp.17-24
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• 2006

In this paper, an algorithm for anchor frame detection in news video is proposed, which consists of four steps. In the first step, the cumulative histogram method is used to detect shot boundaries in order to segment a news video into video shots. In the second step, skin color information is used to detect face regions in each shot boundary. In the third step, color information of upper body regions is used to extract anchor object, which produces candidate anchor frames. Then, from the candidate anchor frames, a graph-theoretic cluster analysis algorithm is utilized to classify the news video into anchor-person frames and non-anchor frames. Experiment results have shown the effectiveness of the proposed algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.6
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• pp.1312-1317
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• 2003

This paper presents an integrated approach to unconstrained face recognition in arbitrary scenes. The front end of the system comprises of a scale and pose tolerant face detector. Scale normalization is achieved through novel combination of a skin color segmentation and log-polar mapping procedure. Principal component analysis is used with the multi-view approach proposed in[10] to handle the pose variations. For a given color input image, the detector encloses a face in a complex scene within a circular boundary and indicates the position of the nose. Next, for recognition, a radial grid mapping centered on the nose yields a feature vector within the circular boundary. As the width of the color segmented region provides an estimated size for the face, the extracted feature vector is scale normalized by the estimated size. The feature vector is input to a trained neural network classifier for face identification. The system was evaluated using a database of 20 person's faces with varying scale and pose obtained on different complex backgrounds. The performance of the face recognizer was also quite good except for sensitivity to small scale face images. The integrated system achieved average recognition rates of 87% to 92%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.9
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• pp.1172-1178
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• 2018

A system that control computer presentations by using the hand motion recognition and identification is proposed. The system recognizes and identifies various types of motion in hand motion, controlls the presentation without additional control devices. To recognize hand movements, it performs a face and hand region detection. Facial area is detected using Haar classifier and hand region is extracted according to skin color information on HSV color model. The face area is used to determine the beginning and end of hand gestures, the size and direction of motion. It recognizes various hand gestures and uses them to control computer presentations according to the hand motion identification rules that are proposed and set horizontal and vertical axes from the face area. It is confirmed that 97.2% recognition rate is obtained in about 1200 hand motion recognition experiments and the proposed algorithm is valid in presentation control.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.851-859
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• 2002

This paper discusses the design of a working system that visually recognizes hand gestures for the control of a window based user interface. We present a method for tracking the fingertip of the index finger using a single camera. Our method is based on CAMSHIFT algorithm and performs better than the CAMSHIFT algorithm in that it tracks well particular hand poses used in the system in complex backgrounds. We describe how the location of the fingertip is mapped to a location on the monitor, and how it Is both necessary and possible to smooth the path of the fingertip location using a physical model of a mouse pointer. Our method is able to track in real time, yet not absorb a major share of computational resources. The performance of our system shows a great promise that we will be able to use this methodology to control computers in near future.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.913-915
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• 2005

임의의 영상에서 얼굴을 검출하는 것은 얼굴을 인식하는데 있어서 선행되어야 할 필수과정이다. 본 논문은 조명의 변화가 심한 컬러영상에서 얼굴을 검출하는 것을 목적으로 한다. 본 논문은 기존의 기하학적 밝기분포 마스크만을 사용한 방법이 조명 변화에 취약한 단점을 보완하는데 중점을 두었다. 히스토그램 평활화(Histogram Equalization : HE)와 감마 크기 보정 (Gamma Intensity Correction : GIC) 방법을 이용해서 조명에 대한 간섭을 줄인 후, 영상 전체에서 피부 영역을 추출하고 이어서 눈 후보들을 검출한다. 검출된 눈 후보들로부터 기하학적 밝기분포 마스크를 적용하여 효과적으로 얼굴 후보들을 찾을 수 있고, 이렇게 찾아진 얼굴 후보들은 주성분분석법(Principal Component Analysis : PCA)를 이용해서 얼굴인지 여부를 판별하게 된다. 본 알고리즘은 조명 밝기 등으로 인해 검출률이 떨어졌던 단점을 보완할 수 있었고, 향후 얼굴 검출 분야에 있어서도 활용 가치가 있을 것으로 생각된다.

• Clinical and Experimental Pediatrics
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• v.45 no.4
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• pp.489-497
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• 2002

Purpose : The objectives of this study were to investigate the causes of chronic cough and to establish the appropriate diagnostic approach to chronic cough in children. Methods : One hundred and thirty two cases of chronic cough were prospectively evaluated. They visitors to pediatric chronic cough clinics at Kang-nam saint Mary's Hospital of Catholic University from August 2000 to July 2001 for 12 months. Careful history taking by questionnaire, physical examination, radiologic studies of chest and sinus, hematologic and immunologic studies, allergic skin tests, and methacholine challenge tests were performed. Color doppler(CD) ultrasonography were performed and compared with simultaneous 24 Hr. esophageal pH monitoring to diagnose gastroesophageal reflux disease(GERD). Results : Age distributions were demonstrated that nine in infants, 82 in early childhood, 38 in late childhood, and three in adolescence. Common causes of chronic cough were bronchial asthma in 40 cases, chronic sinusitis in 22 cases, GERD in seven cases, bronchial asthma combined with sinusitis in 28 cases, bronchial asthma combined with GERD in 14 cases, psychogenic cough in two. cases, foreign body in one case, chronic bronchitis in one case, and bronchiolitis in one case. Comparing with 24 Hr. pH monitoring, sensitivity, specificity, positive predictive value and negative predictive values of CD ultrasonography were 88%, 69%, 85 %, and 73% respectively. Conclusion : The most common causes of chronic cough in children were bronchial asthma, sinusitis and GERD in order. We suggest that CD ultrasonography can be used as a good, convenient screening method for patients with suspected GERD in outpatient settings.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.497-502
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• 2022

Information delivery among young generation has a distinct tendency to prefer visual to text as means of information distribution and sharing recently, and it is natural to distribute information through Youtube or one-man broadcasting on Internet. That is, young generation usually get their information through this kind of distribution procedure. Many young generation are also drastic and more aggressive for decorating themselves very uniquely. It tends to create personal characteristics freely through drastic expression and attempt of face makeup, hair styling and fashion coordination without distinction of sex. Especially, face makeup becomes an object of major concern among males nowadays, and female of course, then it is the major means to express their personality. In this study, to meet the demands of the times, we design and implement the intellectual smart mirror application that efficiently retrieves and recommends the related videos among Youtube or one-man broadcastings produced by famous professional makeup artists to implement the face makeup congruous with our face shape, hair color & style, skin tone, fashion color & style in order to create the face makeup that represent our characteristics. We also introduce the AI technique to provide optimal solution based on the learning of user's search patterns and facial features, and finally provide the detailed makeup face images to give the chance to get the makeup skill stage by stage.