• Proceedings of the Korea Information Processing Society Conference
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• 2008.05a
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• pp.19-21
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• 2008

본 논문에서는 테이블 형이 아닌 스탠드형 테이블 탑 디스플레이에 대한 연구를 다루고 있다. 스크린에 대한 터치를 인식으로 입력을 받아들이므로 TouchFace III 라고 명명하고 있으며, 기존에 개발되었던 두 대의 테이블 탑 디스플레이와는 형태에서 차별을 두고 있다. TouchFace III 시스템은 FTIR(Frustrated Total Internal Reflection : 내부 전반사 장애 현상) 방식이 아닌 TouchLight방식과 HoloWall방식을 조합하여 시스템을 구성하였다. 그래서 스크린에서의 직접적인 손터치 뿐만 아니라, 스크린에 반사되는 손형상에 대한 제스처까지도 인식할 수 있도록 연구중에 있다. 이는 협업을 강조하는 테이블 탑 디스플레이의 컨셉에 어울리며 한 디바이스를 이용하여 동시에 여러사용자가 디바이스를 조작하는 것을 가능하게 한다.

• Fashion & Textile Research Journal
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• v.24 no.6
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• pp.667-685
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• 2022

This paper aims to investigate 4D printing materials for soft robots. 4D printing is a targeted evolution of the 3D printed structure in shape, property, and functionality. It is capable of self-assembly, multi-functionality, and self-repair. In addition, it is time-dependent, printer-independent, and predictable. The shape-shifting behaviors considered in 4D printing include folding, bending, twisting, linear or nonlinear expansion/contraction, surface curling, and generating surface topographical features. The shapes can shift from 1D to 1D, 1D to 2D, 2D to 2D, 1D to 3D, 2D to 3D, and 3D to 3D. In the 4D printing auxetic structure, the kinetiX is a cellular-based material design composed of rigid plates and elastic hinges. In pneumatic auxetics based on the kirigami structure, an inverse optimization method for designing and fabricating morphs three-dimensional shapes out of patterns laid out flat. When 4D printing material is molded into a deformable 3D structure, it can be applied to the exoskeleton material of soft robots such as upper and lower limbs, fingers, hands, toes, and feet. Research on 4D printing materials for soft robots is essential in developing smart clothing for healthcare in the textile and fashion industry.

• The Journal of the Korea Contents Association
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• v.8 no.1
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• pp.212-227
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• 2008

Since 3D face can be rotated freely in 3D space and illumination effects can be modeled properly, 3D face modeling Is more precise and realistic in face pose, illumination, and expression than 2D face modeling. Thus, 3D modeling is necessitated much in face recognition, game, avatar, and etc. In this paper, we propose a 3D face modeling method based on 3D morphable shape modeling. The proposed 3D modeling method first constructs a 3D morphable shape model out of 3D face scan data obtained using a 3D scanner Next, the proposed method extracts and matches feature points of the face from 2D image sequence containing a face to be modeled, and then estimates 3D vertex coordinates of the feature points using a factorization based SfM technique. Then, the proposed method obtains a 3D shape model of the face to be modeled by fitting the 3D vertices to the constructed 3D morphable shape model. Also, the proposed method makes a cylindrical texture map using 2D face image sequence. Finally, the proposed method builds a 3D face model by rendering the 3D face shape model with the cylindrical texture map. Through building processes of 3D face model by the proposed method, it is shown that the proposed method is relatively easy, fast and precise than the previous 3D face model methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.2
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• pp.169-176
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• 2013

To generate the walking path of a humanoid robot in an unknown environment, the shapes of obstacles around the robot should be detected accurately. However, doing so incurs a very large computational cost. Therefore this study proposes a method to classify the obstacle shape into three types: a shape small enough for the robot to go over, a shape planar enough for the robot foot to make contact with, and an uncertain shape that must be avoided by the robot. To classify the obstacle shape, first, the range and the number of the obstacles is detected. If an obstacle can make contact with the robot foot, the shape of an obstacle is accurately derived. If an obstacle has uncertain shape or small size, the shape of an obstacle is not detected to minimize the computational load. Experimental results show that the proposed algorithm efficiently classifies the shapes of obstacles around the robot in real time with low computational load.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1337-1346
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• 2005

In this paper, we describe an algorithm which can automatically recognize human gesture for Human-Robot interaction. In early works, many systems for recognizing human gestures work under many restricted conditions. To eliminate these restrictions, we have proposed the method that can represent 3D and 2D gesture information simultaneously, APM. This method is less sensitive to noise or appearance characteristic. First, the feature vectors are extracted using APM. The next step is constructing a gesture space by analyzing the statistical information of training images with PCA. And then, input images are compared to the model and individually symbolized to one portion of the model space. In the last step, the symbolized images are recognized with HMM as one of model gestures. The experimental results indicate that the proposed algorithm is efficient on gesture recognition, and it is very convenient to apply to humanoid robot or intelligent interface systems.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.2
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• pp.182-189
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• 2014

This paper proposed a framework of recognition and tracking for underwater objects using sonar images as an alternative of underwater optical camera which has the limitation of usage due to turbidity. In Part 1, a design and recognition method for 2D artificial landmark was proposed considering the practical performance of current imaging sonars. In particular, its materials are selected in order to maximize detectability based on characteristics of imaging sonar and ultrasonic waves. It has a simple and omni-directional shape which allows an easy modeling of object, and it includes region based features as identifications. Also, we proposed a real-time recognition algorithm including edge detector, Hough circle transforms, and shape matrix based recognition algorithm. The proposed methods are verified by basin tests using DIDSON.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.06a
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• pp.413-417
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• 2007

Ad hoc 센서 네트워크에서 노드는 제한된 에너지를 가지며, 에너지의 사용률은 토폴로지 구조나 센서 노드의 동작에 의존한다. 본 논문에서는 low power distributed MAC을 개량 하여, MANET에서 clustering 구조의 네트워크를 위한 효율적인 에너지 절약을 위한 새로운 구조를 제안한다. 본 제안된 구조의 특징은 Ad hoc 네트워크에서 에너지에 관련된 배터리 파워나, 노드의 거리, 전송 전력 등의 정보를 활용한 상황 인식을 사용하였다. 에너지 상황 인식을 적용한 제안된 망의 구조는 clustering 형상과 메시지 전송의 성능 및 데이터의 도달 인식을 향성 시킨다. 또한 context aware computing을 이용함으로써, 상황과 정의된 rule에 따라서 노드의 동작과 네크워크 라우팅의 상황에 적응하도록 노드를 조정 할 수 있는 구조이다.

• The Journal of the Acoustical Society of Korea
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• v.19 no.3
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• pp.20-25
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• 2000

This paper proposes the method of surface classification and threshold value selection for surface classification of the three-dimensional object recognition. The processings of three-dimensional image processing system consist of three steps, i.e, acquisition of range data, feature extraction and matching process. This paper proposes the method of shape feature extraction from the acquired rage data in the entire three-dimensional image processing system. In order to achieve these goals, firstly, this article proposes the surface classification method by using the distribution characteristics of sign value from range values. Also pre-existing method which uses the K-curvature and K-curvature has limitation in the practical threshold value selection. To overcome this, this article proposes the selection of threshold value for surface classification. Finally, the effectiveness of this article is demonstrated by the several experiments.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.1
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• pp.27-37
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• 1993

In unmanned machining, One of the most essential issue is the tool management system which includes controlling. identification, presetting and monitoring of cutting tools. Especially the monitoring of tool wear and fracture may be the heart of the system. In this study a computer vision based tool monitoring system is developed. Also an algorithm which can determine the tool condition using this system is presented. In order to enhance practical adaptability the vision system through which two modes of images are taken is located over the rake face of a tool insert. And they are analysed quantitatively and qualitatively with image processing technique. In fact the morphologies of tool fracture or wear are occurred so variously that it is difficult to predict them. For the purpose of this problem the pattern recognition is introduced to classify the modes of the tool such as fracture, crater, chipping and flank wear. The experimental results performed in the CNC turning machine have proved the effectiveness of the proposed system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2008.06a
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• pp.257-262
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• 2008

컴퓨팅 기술의 발전에 따라 선박의 안전항해를 지원하기 위해 Radar, GPS 등 다양한 장비들이 계량, 개발되고 있으며 그들은 선박 항해에 필요한 많은 정보를 제공하고 있다. 하지만 여전히 선박 충돌사고는 끊이지 않고 있으며, 선박 대형화에 힘입어 그 피해도 커지고 있는 실정이다. 이러한 선박 충돌사고는 앞에서 언급한 선박 항해 안전 장비의 성능제약을 받는 야간이나, 해상 환경 악화 시 두드러지게 발생하고 있으며, 특히 제한적인 상황에서 인간의 눈에만 의지해서 항해를 하고 있기 때문이기도 하다. 그래서 이러한 상황에서 Vision기술을 사용하여 카메라를 활용 상대선박을 자동으로 식별하는 시스템을 제안하고자 한다. 이는 선박들이 법적으로 야간이나 각종 장비들이 제한을 받는 상황에서 근처의 다른 선박에게 상황을 전달하기 위해서 등화(불빛)와 형상물을 사용해야한다는 점에서 착안하였다. 제안 시스템을 실제 해상 환경에서 실험하기에 제한점이 많아 프로토타입을 구현하여 실험실 환경에서 실험하고 사용자 평가를 실시하였다. 즉, LED를 가상 등화로 하여 선박에 설치된 것과 동일한 색상과 동일한 위치에 배치하고 이를 카메라를 활용하여 인식 실험을 하였으며 약 90%의 인식률을 보였다. 그리고 이러한 실험화면을 활용하여 항해업무 종사자 15명을 대상으로 사용자 평가를 실시하였으며 대부분의 사람들이 제안된 체계가 해상에서 유용하다고 답변하였다.