• 한국멀티미디어학회논문지
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• 제21권12호
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• pp.1473-1480
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• 2018

The extraction and recognition of human motion characteristics need to combine biometrics to determine and judge human behavior in the movement and distinguish individual identities. The so-called biometric technology, the specific operation is the use of the body's inherent biological characteristics of individual identity authentication, the most noteworthy feature is the invariance and uniqueness. In the past, the behavior recognition technology based on the single characteristic was too restrictive, in this paper, we proposed a mixed feature which combined global silhouette feature and local optical flow feature, and this combined representation was used for human action recognition. And we will use the KTH database to train and test the recognition system. Experiments have been very desirable results.

• 한국정보과학회논문지:소프트웨어및응용
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• 제32권8호
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• pp.759-768
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• 2005

본 논문에서는 다중 혼합 특징 정보를 저 차원 제스처 심볼로 구성하여 제스처를 인식하는 알고리즘에 대해 기술한다. 기존의 기하학적인 특징 기반 방법이나 외관기반 방법에서는 깔, 다리의 위치나 몸의 형상 정보만을 특징 값으로 이용하기 때문에 유사한 신체 동작이나 신체 부위의 움직임에 따라 애매한 결과를 나타내었지만 제안한 방법은 신체의 어느 부위가 움직이는지를 나타내는 부분특징정보(partial feature information)와 전체적인 신체의 형상을 표현하는 전역특징정보(global feature information)를 이용함으로써 동작의 구분뿐만 아니라 유사한 동작을 인식할 수 있는 장점이 있다. 그리고 비교적 적은 계산량과 높은 인식률 때문에 감시 시스템이나 지적 인터페이스 시스템 같은 여러 응용 분야에 적용될 수 있다.

• 한국의류산업학회지
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• 제10권1호
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• pp.92-100
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• 2008

When designing protective clothing, there are something to be considered such as physiological feature of human body, acting range not to restrict physical activity, and effectiveness of material. Because the primary objective of protective clothing is to protect human body from danger and it is designed through complex designing process not likely general clothing design. However, current evaluation techniques-such as the ISO, the ASTM and the CEN, and KS-provide only the standard to evaluate the primary feature of material (testing, performance requirements, material specification, selection and application, test and care, and so on). There are no standard to evaluate influence for the human body while protective clothing put on. Especially, in Korea, there is KS to evaluate protective clothing, but it is partially translated version from ISO because of lack of core technology about this field. However, developed countries recognize it is new competitive means in the time of Global Standards and they are competing to make their own standard to global standard for the protective clothing. Therefore, it can be great opportunity for Korean clothing and textile industry to revitalize if focusing on research and development for protective clothing design based on physical activity of human body, fit evaluation technique and sizing which is currently no global standard for it and developing our standard to global standard.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제9권5호
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• pp.1856-1869
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• 2015

This paper addresses the issues of 3D human activity detection, tracking and recognition from RGB-D video sequences using a feature structured framework. During human tracking and activity recognition, initially, dense depth images are captured using depth camera. In order to track human silhouettes, we considered spatial/temporal continuity, constraints of human motion information and compute centroids of each activity based on chain coding mechanism and centroids point extraction. In body skin joints features, we estimate human body skin color to identify human body parts (i.e., head, hands, and feet) likely to extract joint points information. These joints points are further processed as feature extraction process including distance position features and centroid distance features. Lastly, self-organized maps are used to recognize different activities. Experimental results demonstrate that the proposed method is reliable and efficient in recognizing human poses at different realistic scenes. The proposed system should be applicable to different consumer application systems such as healthcare system, video surveillance system and indoor monitoring systems which track and recognize different activities of multiple users.

• 한국의류산업학회지
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• 제11권5호
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• pp.788-798
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• 2009

This study aims to develop a highly reproducible, optimal frame design algorithm using variations in the curvature of armscye circumference, which will provide the basics for remodeling the 3D human body shape with the concept of reverse design used to develop total contents for the apparel industry. 1. The results of the experiment proved that ratio value was significantly efficient than absolute value of curvature variation to extract feature points in the armscye circumference 2. For the shoulder(1st and 2nd quadrant) and front armhole(3rd quadrant) parts of the armscye circumference, frame remodeling with the positive point of inflection led to the completion of a highly reproducible frame. 3. Similarly, even for the rear armhole part(4th quadrant) in the armscye circumference, it was found that frame remodeling using the positive maximum point of inflection resulted in highly reproducible body shape with the maximum point of inflection situated within the range of split angles $305^{\circ}{\sim}330^{\circ}$, while frame remodeling using simultaneously the two largest points of inflection including maximum point of inflection led to highly reproducible body shape with the maximum point of inflection out of the range $305^{\circ}{\sim}330^{\circ}$. 4. Based upon the optimal frame design algorithm developed in this study, section-specific feature points in the armscye circumference were extracted depending on the rate of curvature variation and remodeling with spline curves was conducted. The results indicate a remarkably high reproducibility(98.6%) and suggest that the algorithm developed in this study is suitable for human body modeling.

• 문화기술의 융합
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• 제5권4호
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• pp.413-420
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• 2019

본 연구의 목적은 기존의 body fat mass 변수와 고콜레스테롤혈증의 연관성연구를 벗어나, 머신러닝기법을 기반으로 body fat mass 변수들의 조합을 이용하여 고콜레스테롤혈증 예측 모델을 개발하는 것이다. 이러한 연구를 위하여 국민건강영양조사 데이터를 기반으로 두 가지 variable selection 메소드와 머신러닝 알고리즘을 이용하여 총 6개의 모델을 생성하였고 질병 예측력을 비교분석하였다. 여러 body fat mass 관련 변수들 중에서 몸통지방량 변수가 고콜레스테롤혈증 예측력이 가장 우수한 변수인 것을 밝혀내었고, 머신러닝 기반 예측모델들 중에서 correlation-based feature subset selection 기반 naive Bayes 알고리즘을 이용한 모델이 0.739의 the area under the receiver operating characteristic curve 값과 0.36의 Matthews correlation coefficient 값을 얻었다. 이러한 연구의 결과는 향후 국내외 대규모 스크리닝 및 대중보건 연구에서 질병예측분야의 중요정보로 활용될 것으로 예상한다.

• 인지과학
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• 제15권1호
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• pp.1-11
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• 2004

본 연구는 만 12-35개월 아동들의 발화에 나타나는 모음 대치 현상에 대한 고찰을 통하여 아동의 모음 체계 구성과 그 변화 과정을 밝히고자 하였다. 또한, 자질별로 모음 대치 현상이 일어나는 비율과 해당 대치음에 대한 산출율을 비교함으로써 분절음 대치 현상과 음 산출 사이의 상관관계 및 분절음 대치 현상의 원인을 함께 검토하였다. 그 결과 혓몸 자질에 의한 모음 변별이 원순성 자질에 의한 모음 변별보다 앞서서 이루어지는 것으로 나타났고, 그 시기는 각각 24개월 무렵과 36개월 이후로 밝혀졌다. 또한 변별이 전혀 안 되던 상태에서 변별이 완전해지는 상태로 이행하는 시기에 두 음소 사이의 일방향적 대치가 두드러지는 현상이 나타나는데, 이러한 현상은 어떤 음이 아동의 음운 체계에서 하나의 음소로 자리 잡기 시작하는 때에 해당 음의 변별적 자질을 다른 음에 확대하는 과잉 적용 현상으로 해석된다.

• 한국정밀공학회지
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• 제16권12호
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• pp.133-142
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• 1999

We introduce the algorithms of 2-D and 3-D position estimation using 2-D vision sensors. The sensors used in this research issue red laser slit light to the body. So, it is very convenient to obtain the coordinates of corner point or edge in sensor coordinate. Since the measured points are normally not fixed in the body coordinate, the additional conditions, that corner lines or edges are straight and fixed in the body coordinate, are used to find out the position and orientation of the body. In the case of 2-D motional body, we can find the solution analytically. But in the case of 3-D motional body, linearization technique and least mean squares method are used because of hard nonlinearity.

• 한국정보통신학회:학술대회논문집
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• 한국정보통신학회 2021년도 추계학술대회
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• pp.226-228
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• 2021

구글사에서 출시된 ML Kit API의 Pose detection를 사용한 영상기반 낙상 알고리즘을 제안한다. Pose detection 알고리듬을 사용하여 추출된 신체의 33개의 3차원 특징점을 활용하여 낙상을 인식한다. 추출된 특징점을 분석하여 낙상을 인식하는 알고리듬은 k-NN을 사용한다. 영상의 크기와 영상내의 인체의 크기에 영향을 받지 않도록 정규화과정을 거치며 특징점들의 상대적인 움직임을 분석하여 낙상을 인식한다. 본 실험을 위해 사용한 13개의 테스트 영상중 13개의 영상에서 낙상을 인식하여 100%의 성공률을 보였다.

• 제어로봇시스템학회논문지
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• 제13권3호
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• pp.235-241
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• 2007

This paper proposes a self-calibration method of robots those are used in industrial assembly lines. The proposed method is a position compensation using laser sensor and vision camera. Because the laser sensor is cross type laser sensor which can scan a horizontal and vertical line, it is efficient way to detect a feature of vehicle and winding shape of vehicle's body. For position compensation of 3-Dimensional axis, we applied block interpolation method. For selecting feature point, pattern matching method is used and 3-D position is selected by Euclidean distance mapping between 462 feature values and evaluated feature point. In order to evaluate the proposed algorithm, experiments are performed in real industrial vehicle assembly line. In results, robot's working point can be displayed 3-D points. These points are used to diagnosis error of position and reselecting working point.