• 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.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.779-784
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• 2008

가상현실 시스템에서 체험자가 현실과 같은 몰입을 느끼기 위해서는 하드웨어를 통한 가상환경 구축과 체험자와의 상호작용이 중요하다. 본 논문에서는 위치 추적 시스템(Motion Tracking System), Wand(3D Mouse) 및 HoloPoint 등 다양한 VR 인터페이스를 통해 체험자의 움직임, 위치, 동작을 인식하고 대형 멀티 디스플레이 시스템을 통해 입체영상을 제공하는 가상환경을 구축하고 체험자가 원하는 정보를 상호작용(Interaction)으로 제공할 수 있는 가상 캠퍼스 안내 시스템을 구현하고자 한다. 가상 캠퍼스 구축은 캠퍼스의 지형, 건물 및 구조물들의 정확한 형상을 얻기 위해 3D 스캐너를 이용하였고 획득된 데이터는 일련의 과정들을 거쳐 3D 모델로 생성된다. 이렇게 생성된 모델을 재배치 및 최적화하기 위해 모델링 소프트웨어를 사용하였다. 구축된 가상 캠퍼스와 위치 추적 시스템 및 Wand의 연동을 위해 VR 프로그래밍 하여 체험자의 움직임 및 동작을 콘텐츠에 그대로 적용시켰다. 여기에 키오스크 유형의 HoloPoint를 이용하여 체험자의 손동작으로 상호작용하는 안내시스템도 구축하였다. 상호작용 가능한 가상캠퍼스 안내 시스템은 가상현실 시스템 구축에 대한 또 다른 방법과 활용 예를 제시함으로써 가상전시관 및 가상체험관 등에 활용될 수 있을 것으로 기대된다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.1
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• pp.102-107
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• 2007

In this paper presents a gesture based driven approach for video editing. Given a lecture video, we adopt novel approaches to automatically detect and synchronize its content with electronic slides. The gestures in each synchronized topic (or shot) are then tracked and recognized continuously. By registering shots and slides md recovering their transformation, the regions where the gestures take place can be known. Based on the recognized gestures and their registered positions, the information in slides can be seamlessly extracted not only to assist video editing, but also to enhance the quality of original lecture video. In experiment with two videos, the proposed system showd each gesture recognition rate 95.5%,96.4%.

• The Journal of the Korea Contents Association
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• v.11 no.10
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• pp.11-18
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• 2011

In the field of image processing to track the fingertip much research has been done. The most common way to calculate the fingertip first, to extract color information. Then, it uses Blob Coloring algorithms which are expressed in blob functions the skin contour and calculates. The algorithm from contour decides the highest location with the fingertip. But this method when measuring it location from the finger condition which bents is not the actual fingertip and has the problem which detects the location which goes wrong. This paper proposes the color space correction algorithm to tracks the fingertip which bents. The method which proposes when tracking the fingertip from the finger condition which bents solves the problem which measures the location which goes wrong. Aim of this paper in compliance with the propensity of the users forecasts a problem in advance and corrects with improvement at the time of height boil an efficiency. Ultimately, this paper suggests empirical application to verify the adequacy and the validity with the proposed method. Accordingly, the satisfaction and the quality of services will be improved the image recognition.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.7
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• pp.1564-1572
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• 2011

In this paper, we propose a new histogram based hand recognition algorithm for augmented reality. Hand recognition system makes it possible a useful interaction between an user and computer. However, there is difficulty in vision-based hand gesture recognition with viewing angle dependency due to the complexity of human hand shape. A new hand recognition system proposed in this paper is based on the features from hand geometry. The proposed recognition system consists of two steps. In the first step, hand region is extracted from the image captured by a camera and then hand gestures are recognized in the second step. At first, we extract hand region by deleting background and using skin color information. Then we recognize hand shape by determining hand feature point using histogram of the obtained hand region. Finally, we design a augmented reality system by controlling a 3D object with the recognized hand gesture. Experimental results show that the proposed algorithm gives more than 91% accuracy for the hand recognition with less computational power.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.621-625
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• 2010

This paper presents a hand motion tracking method for hand gesture interface using a camera in mobile devices such as a smart phone and PDA. When a camera moves according to the hand gesture of the user, global optical flows are generated. Therefore, robust hand movement estimation is possible by considering dominant optical flow based on histogram analysis of the motion direction. A continuous hand gesture is segmented into unit gestures by motion state estimation using motion phase, which is determined by velocity and acceleration of the estimated hand motion. Feature vectors are extracted during movement states and hand gestures are recognized at the end state of each gesture. Support vector machine (SVM), k-nearest neighborhood classifier, and normal Bayes classifier are used for classification. SVM shows 82% recognition rate for 14 hand gestures.

• Journal of Advanced Navigation Technology
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• v.17 no.2
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• pp.240-246
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• 2013

Airtouch technology to integrate the system in the way of information delivery devices, touch screen DID this study is to develop new ways of information delivery systems. Airtouch technology to design and implement a system that can be utilized to view the college campus announcements, education, information, and employment information, and store the remote operation and sharing content, the development of cloud services to sync content via smart technology implementation fusion DID systemto develop. Packs USB interface kinek because you may be used in connection with the information appliances, and low-cost product by leveraging the Kinect sensor, Airtouch technology implementation. Types of input devices paper Airtouch technology systems, the user's hand gestures alone can interact with information appliances, smart fusion system developed by DID by tracking the user's hand movements to manipulate the mouse pointer, and information through the user's hand gestures to command the unit so that you can make. Airtouch technology smart fusion DID system technology utilizing a ripple effect on other industries, such as the online education industry, advertising, information industry increases. Also, replace the existing interface device with the versatility of a wide range of technologies, usability is an infinite expansion.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.11a
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• pp.129-132
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• 2009

컴퓨터의 소형화로 휴대성과 공간의 제약이 없는 컴퓨터 인터페이싱 방법의 필요성이 증가하고 있으며, 이와 관련하여 인간-컴퓨터 상호작용(HCI)을 위한 제스처 기반의 제어방식에 대한 연구가 활발하게 진행되고 있다. 기존의 손동작 인터페이스 구현들은 컴퓨터를 제어하기 위하여 사용방법에 대한 선행학습이 필요하였다. 이 논문은 사용자의 손 모양과 손끝 정보만을 가지고 선행학습이 요구되지 않는 간편한 인터페이스 구현방법을 제안하였다. 이를 위해 1대의 웹캠과 인텔의 오픈소스 영상처리 라이브러리 OpenCv를 사용하였다. 차영상과 화소값 기반의 영상처리과정을 통해 실시간으로 손 영역을 추적하고 이를 이진화 시켰다. 손가락의 움직임도 값이 변하지 않도록 중심모멘트를 설정하여 마우스 커서 움직임을 상대적으로 활용하였다. 상황에 따라 손 끝점을 절대적 좌표로 활용하여 손이 웹캠에서 벋어날 때 움직임을 자연스럽게 연결시켰다. 마지막으로 검지의 움직임 하나 만으로 마우스 클릭 이벤트를 수행함으로써 보다 사용자에게 친숙한 핸드마우스 인터페이스를 구현하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3971-3975
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• 2013

This paper introduces an Augmented Reality system recognizing hand gestures and shows results of the evaluation. The system's user can interact with artificial objects and manipulate their position and motions simply by his hand gestures. Hand gesture recognition is based on Histograms of Oriented Gradients (HOG). Salient features of human hand appearance are detected by HOG blocks. Blocks of different sizes are tested to define the most suitable configuration. To select the most informative blocks for classification multiclass AdaBoostSVM algorithm is applied. Evaluated recognition rate of the algorithm is 94.0%.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.13-16
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• 2002

This paper proposes a method to track hand gesture and to recognize the gesture pattern using Kalman filter and continuous dynamic programming (CDP). The positions of hands are predicted by Kalman filter, and corresponding pixels to the hands are extracted by skin color filter. The center of gravity of the hands is the same as the input pattern vector. The input gesture is then recognized by matching with the reference gesture patterns using CDP. From experimental results to recognize circle shape gesture and intention gestures such as “Come on” and “Bye-bye”, we show the proposed method is feasible to the hand gesture-based human -computer interaction.