• TTA Journal
• /
• s.162
• /
• pp.56-57
• /
• 2015

최근 생체 인증(Biometrics) 기술이 모바일 핀테크(Fin-TECH)와 결합하면서 '화려한 부활'을 꿈꾸고 있다. 출입 통제, 근태 관리 등 일부 특수 보안 용도에 머물던 생체 인증이 모바일 결제의 새로운 본인인증 서비스로 잇따라 채택되면서 대중화의 물꼬를 트기 시작한 것. 생체 인증은 사람마다 고유한 신체적 특징을 '암호'로 사용해 개인을 인증하는 기술이다. '생체 인식'으로 불리기도 한다. 이제 지문을 넘어 홍채, 손 모양, 혈관 구조, 얼굴, 목소리, 심박 수, 뇌파 등 다양해지고 있는 추세다.

• Journal of Korea Multimedia Society
• /
• v.15 no.10
• /
• pp.1196-1204
• /
• 2012

In this paper, a series of algorithms are proposed for controlling different kinds of multimedia contents and realizing interact between human and computer by using single input device. Human gesture recognition based on NUI is presented firstly in my paper. Since the image information we get it from camera is not sensitive for further processing, we transform it to YCbCr color space, and then morphological processing algorithm is used to delete unuseful noise. Boundary Energy and depth information is extracted for hand detection. After we receive the image of hand detection, PCA algorithm is used to recognize hand posture, difference image and moment method are used to detect hand centroid and extract trajectory of hand movement. 8 direction codes are defined for quantifying gesture trajectory, so the symbol value will be affirmed. Furthermore, HMM algorithm is used for hand gesture recognition based on the symbol value. According to series of methods we presented, we can control multimedia contents by using human gesture recognition. Through large numbers of experiments, the algorithms we presented have satisfying performance, hand detection rate is up to 94.25%, gesture recognition rate exceed 92.6%, hand posture recognition rate can achieve 85.86%, and face detection rate is up to 89.58%. According to these experiment results, we can control many kinds of multimedia contents on computer effectively, such as video player, MP3, e-book and so on.

• Journal of Broadcast Engineering
• /
• v.19 no.6
• /
• pp.942-956
• /
• 2014

This paper proposes a real-time hand pose tracking method using a monocular RGB camera. Hand tracking has high ambiguity since a hand has a number of degrees of freedom. Thus, to reduce the ambiguity the proposed method adopts the step-by-step estimation scheme: a palm pose estimation, a finger yaw motion estimation, and a finger pitch motion estimation, which are performed in consecutive order. Assuming a hand to be a plane, the proposed method utilizes a planar hand model, which facilitates a hand model regeneration. The hand model regeneration modifies the hand model to fit a current user's hand, and improves robustness and accuracy of the tracking results. The proposed method can work in real-time and does not require GPU-based processing. Thus, it can be applied to various platforms including mobile devices such as Google Glass. The effectiveness and performance of the proposed method will be verified through various experiments.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.23 no.6
• /
• pp.551-557
• /
• 2013

In intelligent robot research, hand gesture recognition has been an important issue. And techniques that recognize simple gestures are commercialized in smart phone, smart TV for swiping screen or volume control. For gesture recognition, robust hand detection is important and necessary but it is challenging because hand shape is complex and hard to be detected in cluttered background, variant illumination. In this paper, we propose efficient hand detection algorithm for detecting pointing hand for recognition of place where user pointed. To minimize false detections, ROIs are generated within the compact search region using skin color detection result. The ROIs are verified by HOG-SVM and pointing direction is computed by both detection results of head-shoulder and hand. In experiment, it is shown that proposed method shows good performance for hand detection.

• Proceedings of the KIEE Conference
• /
• 2008.10b
• /
• pp.327-328
• /
• 2008

로봇과 상호 작용하기 위한 수단으로 손동작 인식 시스템이 많이 사용되고 있으며, 본 논문에서는 손에 부가적인 장치를 장착하지 않은 상태에서 영상 처리를 이용하여 손동작을 인식하는 시스템을 구현하였다. 먼저 로봇은 영상 입력 장치로써 웹캠을 사용하고, 손 영상을 스킨 컬러를 바탕으로 영상 처리를 하여 추출해내고, 그 이미지를 분석하여 그 모양이 가위인지 바위인지 보인지 인식한다. 가위 바위 보 게임을 위하여 로봇이 손동작을 표현할 수 있도록 손가락이 네 개인 손을 설계 및 구현하였다. 이때, 기존의 와이어 방식이 아닌 제어를 이용한 손가락을 설계하였고, 각각의 손가락이 독립적으로 제어될 수 있기 때문에 가위 바위 보의 손동작을 표현할 수 있다. 그리고 음성 인식을 이용하여 사람과 동시에 가위 바위 보 중 하나를 결정한 후 표현하기 때문에 가위 바위 보 게임이 가능하다. 뿐만 아니라 로봇이 승패도 알 수 있다.

• The Journal of the Korea Contents Association
• /
• v.10 no.5
• /
• pp.20-28
• /
• 2010

In this paper, we propose a hand gesture interface for the manipulation of augmented objects in 3D space using a camera. Generally a marker is used for the detection of 3D movement in 2D images. However marker based system has obvious defects since markers are always to be included in the image or we need additional equipments for controling objects, which results in reduced immersion. To overcome this problem, we replace marker by planar hand shape by estimating the hand pose. Kalman filter is for robust tracking of the hand shape. The experimental result indicates the feasibility of the proposed algorithm for hand based AR interfaces.

• Journal of Korea Game Society
• /
• v.20 no.5
• /
• pp.31-40
• /
• 2020

The effects of two different types of haptic feedback(one-hand versus two-hand haptic feedback) on interactivity and body ownership were investigated in the virtual reality setting through an experiment. Using within-subject design, participants performed the task of hitting and destroying a ball-shaped object in virtual reality for both, one-hand and two-hand haptic feedback conditions. The results showed that participants tended to report a higher level of interactivity when using two-hand haptic feedback, whereas there was no difference between the two conditions in a sense of body ownership.

• Journal of Broadcast Engineering
• /
• v.19 no.1
• /
• pp.83-95
• /
• 2014

Hand posture recognition is an important technique to enable a natural and familiar interface in HCI(human computer interaction) field. In this paper, we introduce a hand posture recognition method by using a depth camera. Moreover, the hand posture recognition method is incorporated with MPEG-U based advanced user interaction (AUI) interface system, which can provide a natural interface with a variety of devices. The proposed method initially detects positions and lengths of all fingers opened and then it recognizes hand posture from pose of one or two hands and the number of fingers folded when user takes a gesture representing a pattern of AUI data format specified in the MPEG-U part 2. The AUI interface system represents user's hand posture as compliant MPEG-U schema structure. Experimental results show performance of the hand posture recognition and it is verified that the AUI interface system is compatible with the MPEG-U standard.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.14 no.4
• /
• pp.506-511
• /
• 2004

Biometrics is getting more and more attention in recent years for security and other concerns. So far, only fingerprint recognition has seen limited success for on-line security check, since other biometrics verification and identification systems require more complicated and expensive acquisition interfaces and recognition processes. Hand-Geometry has been used for biometric verification and identification because of its acquisition convenience and good performance for verification and identification performance. Hence, it can be a good candidate for online checks. Therefore, this paper proposes a Hand-Geometry recognition system based on geometrical features of hand. From anatomical point of view, human hand can be characterized by its length, width, thickness, geometrical composition, shapes of the palm, and shape and geometry of the fingers. This paper proposes thirty relevant features for a Hand-Geometry recognition system. However, during experimentation, it was discovered that length measured from the tip of the finger was not a reliable feature. Hence, we propose a new technique based on Genetic Algorithm for extraction of the center of nail bottom, in order to use it for the length feature.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.10
• /
• pp.171-180
• /
• 2013

Generally, when we apply zernike moments value for matching, we can use those moments value obtained from projecting image information under circumscribed circle to zernike basis function. However, the problem is that the power of discrimination can be reduced because hand images include lots of overlapped information due to its special characteristic. On the other hand, when distinguishing hand poses, information in specific area of image information except for overlapped information can increase the power of discrimination. In this paper, in order to solve problems like those, we design R3 ring mask by combining image obtained from R2 ring mask, which can weight information of the power of discrimination and image obtained from R1 ring mask, which eliminate the overlapped information. The moments which are obtained by R3 ring mask decrease operational time by reducing dimension through principle component analysis. In order to confirm the superiority of the suggested method, we conducted some experiments by comparing our method to other method using seven different hand poses.