• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2014.06a
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• pp.34-35
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• 2014

본 논문에서는 손가락 제스처 인식을 위해서 깊이 영상 카메라를 이용하여 손 영역을 추적하고 손가락 끝점을 찾는 방법을 제시하고자 한다. 실시간 영역 추적을 위해 적은 연산량으로 손 영역의 중심점을 검출하고 추적이 가능하여야 하며, 다양한 제스처를 효과적으로 인식하기 위해서는 손 모양에서 손가락을 인식하여야 하기 때문에 손가락 끝점을 찾는 방법도 함꼐 제시하고자 한다. 또한 손가락이 정확히 검출되었는지를 확인하기 위해서 손가락의 이동과 손가락의 클릭 제스처를 마우스에 연동하여 검출 결과를 테스트 하였다.

• 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.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.07a
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• pp.31-34
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• 2022

본 논문에서는 손목 부착형 웨어러블(Wearable) RGB 카메라를 통해 취득한 손 이미지에 최적화된 손 자세 추정모델과 학습방법을 제안한다. 최근 의료분야에서 활발하게 인공지능이 사용되고 있으며 그 중 이미지 인식을 중심으로 하는 진단 분야[1]가 괄목할만한 성과를 보인다. 본 연구에서는 웨어러블 카메라를 통해 얻은 손 자세를 활용하여 질병 진단에 적용할 계획이다. 또한, 본 연구수행을 통해 질병진단에 필요한 데이터 측정비용 절감 및 개인 맞춤형 진단서비스를 제공할 것으로 기대된다.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.300-306
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• 2012

In this paper, we propose a vision based hand motion recognition method for an untouchable user interface of smart devices. First, an original color image is converted into a gray scaled image and its spacial resolution is reduced, taking the small memory and low computational power of smart devices into consideration. For robust recognition of hand motions through separation of horizontal and vertical motions, the horizontal principal area (HPA) and the vertical principal area (VPA) are defined respectively. From the difference images of the consecutively obtained images, the center of gravity (CoG) of the significantly changed pixels caused by hand motions is obtained, and the direction of hand motion is detected by defining the least mean squared line for the CoG in time. For verifying the feasibility of the proposed method, the experiments are carried out with a vision system.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.10
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• pp.713-722
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• 2013

This paper proposes a method of using depth information to detect the hand region in real-time based on the cascade method. In order to ensure stable and speedy detection of the hand region even under conditions of lighting changes in the test environment, this study uses only features based on depth information, and proposes a method of detecting the hand region by means of a classifier that uses boosting and cascading methods. First, in order to extract features using only depth information, we calculate the difference between the depth value at the center of the input image and the average of depth value within the segmented block, and to ensure that hand regions of all sizes will be detected, we use the central depth value and the second order linear model to predict the size of the hand region. The cascade method is applied to implement training and recognition by extracting features from the hand region. The classifier proposed in this paper maintains accuracy and enhances speed by composing each stage into a single weak classifier and obtaining the threshold value that satisfies the detection rate while exhibiting the lowest error rate to perform over-fitting training. The trained classifier is used to classify the hand region, and detects the final hand region in the final merger stage. Lastly, to verify performance, we perform quantitative and qualitative comparative analyses with various conventional AdaBoost algorithms to confirm the efficiency of the hand region detection algorithm proposed in this paper.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.05a
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• pp.586-589
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• 2015

A computer presentation system by using hand-motion identification rules is proposed. To identify hand motions of a presenter, a face region is extracted first using haar classifier. A motion status(patterns) and position of hands is discriminated using the center of gravities of user's face and hand after segmenting the hand area on the YCbCr color model. User's hand is applied to the motion detection rules and then presentation control command is then executed. The proposed system utilizes the motion identification rules without the use of additional equipment and it is then capable of controlling the presentation and does not depend on the complexity of the background. The proposed algorithm confirmed the stable control operation via the presentation of the experiment in the dark illumination range of indoor atmosphere (lx) 15-20-30.

• The Journal of the Korea Contents Association
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• v.22 no.1
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• pp.116-125
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• 2022

Netflix Original movies have distinctive characteristics in that it is screened online only and viewers have to watch movies using their personal devices. By analyzing the haptic characteristics of Netflix platform from remediation perspective, we examine how Netflix hypermediacy haptic characteristics associated with clicking or touching expand to immediacy haptic characteristics, and compare the differences between Netflix original movie (2020) and film movie (1940). Through this, it points out the connection between the sense of the hand that requires clicking or touching and the description of the hand in Netflix original movie . As the individual interface of the personal device has been adjusted to make it possible to watch movies, the position of the hand becomes important in watching movies, and the hand plays an essential role in the beginning, middle, and end of the movie. Therefore, this study, which focuses on the haptic characteristics of Netflix original movie , is meaningful in that it studied the characteristics of the OTT original movie that was not previously covered and that the haptic characteristic plays an important role in the way of watching OTT contents.

• Journal of Korea Multimedia Society
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• v.13 no.2
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• pp.316-323
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• 2010

In this paper, we propose fingertip extraction and hand motion recognition method for augmented reality applications. First, an input image is transformed into HSV color space from RGB color space. A hand area is segmented using double thresholding of H, S value, region growing, and connected component analysis. Next, the end points of the index finger and thumb are extracted using morphology operation and subtraction for a virtual keyboard and mouse interface. Finally, the angle between the end points of the index finger and thumb with respect to the center of mass point of the palm is calculated to detect the touch between the index finger and thumb for implementing the click of a mouse button. Experimental results on various input images showed that our method segments the hand, fingertips, and recognizes the movements of the hand fast and accurately. Proposed methods can be used the input interface for augmented reality applications.

• The Journal of the Korean dental association
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• v.16 no.12 s.115
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• pp.888-888
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• 1978

• 대학교육
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• s.23
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• pp.41-51
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• 1986