• 패션정보와 기술
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• 제1권
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• pp.96-100
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• 2004

• International Journal of Human Ecology
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• 제9권1호
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• pp.97-106
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• 2008

This study investigated the relationships between eating disorder risk, body image perception, weight control, and dietary habits in Korean women. Body shape perception, the Eating Attitude Test (EAT-26) and dietary habit information were collected by a self-administered questionnaire to 373 adult women and the data were analyzed by the Chi-square test. 31.4% of the women were classified in the eating disorder group by a score of over 20 points on the EAT-26. Compared to the normal group, more women in the eating disorder risk group perceived that a thin body shape was the ideal body shape and were dissatisfied with their body shape. This group was also more interested in weight control and more likely to try weight control methods. The eating disorder risk group was more likely to skip meals and snacks than the normal group. In addition, they had a greater appetite and a higher frequency of overeating than the normal group. Over 30% of the Korean women surveyed were categorized at high risk of eating disorders. They were more likely to overestimate body weight and shape and tried to control their weight by inappropriate methods. To prevent eating disorders in adult women, nutrition education programs should incorporate strategies to change inaccurate self-body image and to disseminate information about healthy weight control methods.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2002년도 하계종합학술대회 논문집(3)
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• pp.199-202
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• 2002

We described a real-time 3D computer vision system called MIMIC(Motion interface f Motion information Capture system) that can capture and save motion of an actor. This system analyzes input images from vision sensors and searches feature information like a head, hands, and feet. Moreover, this estimates intermediated joints as an elbow and hee using feature information and makes 3D human model having 20 joints. This virtual human model mimics the motion of an actor in real-time. Therefore this system can realize the movement of an actor unaffectedly because of making intermediated joint for complete human body contrary to other marker-free motion capture system.

• Journal of Information Processing Systems
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• 제8권3호
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• pp.483-494
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• 2012

Many recent events, such as terrorist attacks, exposed defects in most sophisticated security systems. Therefore, it is necessary to improve security data systems based on the body or behavioral characteristics, often called biometrics. Together with the growing interest in the development of human and computer interface and biometric identification, human face recognition has become an active research area. Face recognition appears to offer several advantages over other biometric methods. Nowadays, Principal Component Analysis (PCA) has been widely adopted for the face recognition algorithm. Yet still, PCA has limitations such as poor discriminatory power and large computational load. This paper proposes a novel algorithm for face recognition using a mid band frequency component of partial information which is used for PCA representation. Because the human face has even symmetry, half of a face is sufficient for face recognition. This partial information saves storage and computation time. In comparison with the traditional use of PCA, the proposed method gives better recognition accuracy and discriminatory power. Furthermore, the proposed method reduces the computational load and storage significantly.

• 한국통신학회논문지
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• 제34권10B호
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• pp.981-987
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• 2009

최근 유비쿼터스 헬스케어 서비스를 위한 무선 신체 망에 대한 연구가 IEEE 등을 중심으로 연구가 활발히 진행되고 있다. 무선 신체망은 전력제한 및 생체특성을 반영하여 멀티 홉 통신 기반의 부모노드 및 자식노드로 구성된 트리형태로 구성되는 경우가 많다. 이 경우 기존의 센서 네트워크와 달리 빈번한 신체의 움직임으로 망에 연결되어 있는 노드의 연결이 끊어질 가능성이 높으며 각 노드의 전력소모 제한으로 인해 각 노드에서 처리 가능한 노드 연결 수에 제한이 있다. 본 연구에서는 노드가 망과 연결이 끊어졌을 경우 노드가 전송할 패킷의 우선순위를 고려하여 QoS를 만족하면서 최적의 부모 노드를 선택하는 휴리스틱 알고리즘을 제안한다. 시뮬레이션을 통해 제안한 알고리즘의 성능분석을 하였으며 그 결과 본 연구에서 제안한 알고리즘이 망의 생존시간이 더 길다는 것을 확인하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권11호
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• pp.2824-2838
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• 2013

There has been a lot of attention paid recently to analyze dynamic human gestures that vary over time. Most attention to dynamic gestures concerns with spatio-temporal features, as compared to analyzing each frame of gestures separately. For accurate dynamic gesture recognition, motion feature extraction algorithms need to find representative features that uniquely identify time-varying gestures. This paper proposes a new feature-extraction algorithm using temporal self-similarity based on a hierarchical human model. Because a conventional temporal self-similarity method computes a whole movement among the continuous frames, the conventional temporal self-similarity method cannot recognize different gestures with the same amount of movement. The proposed model-based temporal self-similarity method groups body parts of a hierarchical model into several sets and calculates movements for each set. While recognition results can depend on how the sets are made, the best way to find optimal sets is to separate frequently used body parts from less-used body parts. Then, we apply a multiclass support vector machine whose optimization algorithm is based on structural support vector machines. In this paper, the effectiveness of the proposed feature extraction algorithm is demonstrated in an application for taebo gesture recognition. We show that the model-based temporal self-similarity method can overcome the shortcomings of the conventional temporal self-similarity method and the recognition results of the model-based method are superior to that of the conventional method.

• 동아시아식생활학회지
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• 제21권4호
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• pp.587-599
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• 2011

The purpose of this study was to examine self-perception of body image and dieting behaviors by gender among high school students. The data were collected by a self-administered questionnaire during April, 2010, and analyzed by SPSS Windows V.18.0. The results were as follows. First, many respondents showed a desire to be underweight and regarded themselves as overweight, even though they had a normal BMI. Second, female respondents showed a higher level of concern about diet than male respondents. Third, male respondents received information about diet mostly from their family or friends, whereas female respondents received information from blogs, mini-homepages, or Kin-search on the Internet. Finally, female respondents showed a higher level of practice for fasting therapy than male respondents, whereas male respondents showed a higher level of practice for food therapy, drug therapy, oriental medicine therapy, and steam bath therapy. Therefore, high school should educate students to get right recognition and knowledge of diet.

• 한국멀티미디어학회논문지
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• 제19권1호
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• pp.68-79
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• 2016

Electromyographic (EMG) signals have been widely used as motion commands of prosthetic arms. Although EMG signals contain meaningful information including the movement intentions of human body, it is difficult to predict the subject's motion by analyzing EMG signals in real-time due to the difficulties in extracting motion information from the signals including a lot of noises inherently. In this paper, four Ag/AgCl electrodes are placed on the surface of the subject's major muscles which are in charge of four upper arm movements (wrist flexion, wrist extension, ulnar deviation, finger flexion) to measure EMG signals corresponding to the movements. The measured signals are sampled using DAQ module and clustered sequentially. The Fuzzy C-Means (FCMs) method calculates the center values of the clustered data group. The fuzzy system designed to detect the upper arm movement intention utilizing the center values as input signals shows about 90% success in classifying the movement intentions.

• 한국정보과학회논문지:소프트웨어및응용
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• 제34권10호
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• pp.937-944
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• 2007

본 논문은 스테레오 카메라를 이용한 이동 카메라 환경에서Mean Shift와 깊이지도를 결합하여 다수의 사람을 다양한 자세, 크기, 조명변화에 강인한 추적을 하는 방법을 제안한다. Mean Shift 추적 알고리즘은 빠르고 안정적인 성능으로 실시간 추적에 적합하다. 그러나 객체의 칼라 정보만으로는 배경과 칼라 분포가 유사한 객체의 경우 추적에 실패할 수 있는 단점을 보완하기 위하여 깊이 정보를 결합하는 방법을 제안한다. 또한 객체가 이동하면서 발생하는 가려짐 문제를 해결하기 위하여 검출된 사람 영역을 머리, 몸통, 다리로 나누어 신체 부위별 모델링을 하였고 박스 크기가 객체의 크기변화에 따라 적응적으로 변하도록 하였다. 본 논문에서 제안하는 알고리즘은 다양한 데이타에 대해서 실험한 결과 정확한 검출과 추적에 우수한 성능을 확인 할 수 있었다.

• 한국산업정보학회논문지
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• 제24권5호
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• pp.17-25
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• 2019

본 논문은 단일 이미지를 패션쇼 워킹 영상으로 변환하는 기술을 소개한다. 일반인이 가상으로 패션모델이 되어 보는 흥미로운 응용일 뿐 아니라, 나아가 가상 착용기술과 함께 결합하게 되면 의상착용결과의 동적인 확인이 가능한 기술이다. 본 논문에서 사용한 기술은 이미지에서 3차원 인간신체 모델을 추정 복원해 주는 SMPLify 기법에 기초하여, 인체 모델에서 의상을 포함한 사람으로 모델을 확장하고, 이에 애니메이션 기법을 적용하여 구현되었다. 인체와 의상을 포한한 사람의 3차원 모델은 2차원 이미지 상에서 기하변형과 깊이정보를 사용하여 복원하였다. 패션 데이터 셋에 적용해 본 결과 정자세의 경우에는 성공적인 수준의 결과를 보였으나, 상용수준의 성능을 위해서는 이미지의 분할 기술, 매핑기술 및 가려진 영역의 복원기술 등 선 후처리 기술에 보완이 필요한 것으로 확인되었다.