• Journal of Korean Medical classics
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• v.25 no.4
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• pp.105-113
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• 2012

Objectives : Acquiring information from symptoms is one of the important method to gain clinically available information in korean medicine. Therefore, up to now, study of symptom terms was frequently implemented in promotion of various information project. In data extraction methods using symptom information from DB, information search using synonym and method using ontology is studied and utilized. However, considering concept of symptom has essential information of appeared body area and phenomenon we think that extending synonym and ontology relationship in symptom terms can be useful for search and set to this study. Methods : We collect terms relevant to human body area and structure described in Donguibogam. Synonymous relationship between collected terms is organized. Relationship between collected terms is build to human-body-knowledge table which has form of Concept+Relation+Concept. Type of relationship is limited on a range of expressing content about parts of human body. Result & Conclusion : Search condition is generated automatically using relationship of the upper area in knowledge table contents. Information of next and previous acupuncture point, upper and lower acupuncture point, left and right acupuncture point can be searched using information of acupuncture point location, order, relative position in area, direction in knowledge table contents.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.171.5-171
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• 2001

Information that is acquired by adhered sensors on a body has been commonly used for the three-dimensional real-time motion capture algorithm. This paper describes realtime motion capture algorithm using computer vision. In a real-time image sequence, human body silhouette is extracted use a background subtraction between background image and the reference image. Then a human standing posture whether forward or backward is estimated by extraction of skin region in the silhoutte. After then, the principal axis is calculated in the torso and the face region is estimated on the principal axis. Feature points, which are essential condition to track the human gesture, are obtained ...

• Biomedical Science Letters
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• v.15 no.3
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• pp.187-197
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• 2009

Fingerprinting is a frontier technique that is the most frequently applied for human identification throughout the world. All citizens over 17 year old living in the Republic of Korea must be fingerprinted to obtain a certificate of resident registration. In Korea, for this reason, human identification through fingerprints has been far better developed and used efficiently both in crime scene investigation and in confirmation of an unidentified body. Scientific approaches have been made to accurately extract the metamorphosed fingerprints in various environments. Because most of the studies on fingerprinting have been accomplished with biometric techniques, researches on restoration of human dermal tissue and taking custody data after collecting fingerprints have been comparatively undermined. In this study, a newly innovative method for fingerprint extraction was developed using the polyester film with print powders and the high temperature-moisturizing method. Compared to the conventional fingerprinting method of paper with ink, minutiae numbers of fingerprints were greatly increased in polyester film with print powders after restoration of fingertips by high temperature-moisturization. This newly developed procedure would be an efficient fingerprinting technique which could be utilized in scientific investigation and in personal identification in the future. Furthermore, the new method for restoration and extraction of fingerprints are easy and inexpensive to practice for a number of human identification.

• Journal of the Ergonomics Society of Korea
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• v.24 no.2
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• pp.35-43
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• 2005

The purpose of this study is to suggest computer assisted neck-base's landmark identification algorithms and measurement extraction methods from three-dimensional human scan data. So we developed the algorithms for automatic identification of landmarks related to the neck-base types. The subjects were 58 women $18{\sim}24$ years of age. Their body were measured directly and indirectly by using camera and three-dimensional body scanner. They were measured during the months of October in 2001. Based on the characters of classified neck-base types, algorithms for the automatic identification of landmarks and methods of automatic measurement are developed. The three-dimensional automatic measuring program is made by $C^{++}$ language. Using this program, 4 landmarks are identified and 6 items are measured. In the verifying the precision of automatic measurement, the height measurements(cervicale, side neck point, front neck point) were relatively accurate, but neck-base width measurement was measured wide.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.6
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• pp.411-414
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• 2018

In this paper, we propose a radar image extraction scheme for frequency modulated continuous wave radar-based human motion indication. We extracted three-dimensional(3D) range-velocity-angle spectra and generated three micro-profile images by compressing the 3D images in all three directions in every frame. Furthermore, we used body echo suppression to make use of the weak reelection such as in hands and arms. By applying the complete images to classifiers, various human motions can be indicated.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.248-251
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• 1995

Nowadays, the internal images of a human body can be easily provided by the ultrasound imaging, the X-ray CT, or the MRI device, among which the ultrasound imaging device has good resolution for soft tissues of a human body compared with the other devices. Furthermore, the use of ultrasound imaging devices will increase in future especially in the obstetrics, territory, since it does not give harm to the human body. Although several techniques have been investigated until now in order to extract organs from ultrasound images, very few of them have achieved satisfactory results because of low contrast and high noise nature of images. This paper proposes a technique for automatic extraction of the gall bladder area from ultrasound images. The proposed technique first extracts a small reliable area of a gall bladder from an ultrasound image employing smoothing, binarization, expanding and shrinking, and labeling, and then expands the area referring to the binarized version of the original image. The technique is examined its performance by real ultrasound images of a gall bladder and satisfactory results are obtained. Some problems to be solved are discussed finally.

• Journal of Korea Multimedia Society
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• v.21 no.4
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• pp.478-484
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• 2018

The choice of the motion features influences the result of the human action recognition method directly. Many factors often influence the single feature differently, such as appearance of the human body, environment and video camera. So the accuracy of action recognition is restricted. On the bases of studying the representation and recognition of human actions, and giving fully consideration to the advantages and disadvantages of different features, the Dense Trajectories(DT) algorithm is a very classic algorithm in the field of behavior recognition feature extraction, but there are some defects in the use of optical flow images. In this paper, we will use the improved Dense Trajectories(iDT) algorithm to optimize and extract the optical flow features in the movement of human action, then we will combined with Support Vector Machine methods to identify human behavior, and use the image in the KTH database for training and testing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.6C
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• pp.593-603
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• 2009

In this paper, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with an active stereo camera. The proposed system consists of three modules: detection, tracking and silhouette extraction. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap is estimated in advance and then this was effectively incorporated into the graph cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data and it was shown to detect and track multiple people very well and also produce high quality silhouettes. The proposed system can assist in gesture and gait recognition in field of Human-Robot Interaction (HRI).

• Journal of Information Science Theory and Practice
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• v.6 no.4
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• pp.28-38
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• 2018

Wikipedia is composed of millions of articles, each of which explains a particular entity with various languages in the real world. Since the articles are contributed and edited by a large population of diverse experts with no specific authority, Wikipedia can be seen as a naturally occurring body of human knowledge. In this paper, we propose a method to automatically identify key entities and relations in Wikipedia articles, which can be used for automatic ontology construction. Compared to previous approaches to entity and relation extraction and/or identification from text, our goal is to capture naturally occurring entities and relations from Wikipedia while minimizing artificiality often introduced at the stages of constructing training and testing data. The titles of the articles and anchored phrases in their text are regarded as entities, and their types are automatically classified with minimal training. We attempt to automatically detect and identify possible relations among the entities based on clustering without training data, as opposed to the relation extraction approach that focuses on improvement of accuracy in selecting one of the several target relations for a given pair of entities. While the relation extraction approach with supervised learning requires a significant amount of annotation efforts for a predefined set of relations, our approach attempts to discover relations as they occur naturally. Unlike other unsupervised relation identification work where evaluation of automatically identified relations is done with the correct relations determined a priori by human judges, we attempted to evaluate appropriateness of the naturally occurring clusters of relations involving person-artifact and person-organization entities and their relation names.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2006.11a
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• pp.348-351
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• 2006

영상을 통한 감정 인식 기술은 사회의 여러 분야에서 필요성이 대두되고 있음에도 불구하고 인식 과정의 어려움으로 인해 풀리지 않는 문제로 남아 있다. 인간의 움직임을 이용한 감정 인식 기술은 많은 응용이 가능하기 때문에 개발의 필요성이 증대되고 있다. 영상을 통해 감정을 인식하는 시스템은 매우 다양한 기법들이 사용되는 복합적인 시스템이다. 본 논문에서는 이전에 연구된 움직임 추출 방법들을 바탕으로 한 새로운 감정 인식 시스템을 제안한다. 제안된 시스템은 은닉 마르코프 모델을 통해 동정된 분류기를 이용하여 감정을 인식한다. 제안된 시스템의 성능을 평가하기 위해 평가데이터 베이스가 구축되었으며, 이를 통해 제안된 감정 인식 시스템의 성능을 확인하였다.