• 한국멀티미디어학회논문지
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• 제22권4호
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• pp.424-431
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• 2019

In this paper, we propose a real-time hand gesture recognition algorithm to eliminate the inconvenience of using hand controllers in VR applications. The user's 3D hand coordinate information is detected by leap motion sensor and then the coordinates are generated into two dimensional image. We classify hand gestures in real-time by learning the imaged 3D hand coordinate information through SSD(Single Shot multibox Detector) model which is one of CNN(Convolutional Neural Networks) models. We propose to use all 3 channels rather than only one channel. A sliding window technique is also proposed to recognize the gesture in real time when the user actually makes a gesture. An experiment was conducted to measure the recognition rate and learning performance of the proposed model. Our proposed model showed 99.88% recognition accuracy and showed higher usability than the existing algorithm.

• 한국인터넷방송통신학회논문지
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• 제19권2호
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• pp.143-149
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• 2019

플로팅 홀로그램은 광고나 콘서트와 같이 넓은 공간에서 현장감과 실존감이 뛰어난 3D 입체영상을 제공하면서, 3D 안경의 불편함, 시각적 피로, 공간 왜곡 현상 발생을 감소할 수 있는 기술이다. 따라서 본 논문은 좁은 공간에서도 사용가능한 플로팅 홀로그램 환경에서 캐릭터 조작을 위한 사용자 제스처 인식 시스템을 구현한다. 제안된 방법은 하르 특징기반의 캐시케이드((Harr feature-based cascade classifier) 분류기를 이용하여 얼굴 영역을 검출하고, 검출된 얼굴 영역을 기준으로 실시간으로 체스쳐 차영상으로부터 사용자 제스쳐의 발생 위치 정보를 이용하여 사용자 제스쳐를 인식한다. 그리고 각각 인식된 제스쳐 정보는 플로팅 홀로그램 환경에서 생성된 캐릭터 움직임을 조작하기 위하여 상응하는 행위에 맵핑된다. 제안된 플로팅 홀로그램 캐릭터 조작을 위한 사용자 제스처 인식 시스템의 성능평가를 위해서는 플로팅 홀로그램 디스플레이 장치를 제작하고, 몸 흔들기, 걷기, 손 흔들기, 점프 등의 각 제스처에 따른 인식률을 반복 측정한 결과 평균 88%의 인식률을 보였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제15권3호
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• pp.186-191
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• 2015

Hand gesture is the most common tool used to interact with and control various electronic devices. In this paper, we propose a novel hand gesture recognition method using fuzzy logic based classification with a new type of sensor array. In some cases, feature patterns of hand gesture signals cannot be uniquely distinguished and recognized when people perform the same gesture in different ways. Moreover, differences in the hand shape and skeletal articulation of the arm influence to the process. Manifold features were extracted, and efficient features, which make gestures distinguishable, were selected. However, there exist similar feature patterns across different hand gestures, and fuzzy logic is applied to classify them. Fuzzy rules are defined based on the many feature patterns of the input signal. An adaptive neural fuzzy inference system was used to generate fuzzy rules automatically for classifying hand gestures using low number of feature patterns as input. In addition, emotion expression was conducted after the hand gesture recognition for resultant human-robot interaction. Our proposed method was tested with many hand gesture datasets and validated with different evaluation metrics. Experimental results show that our method detects more hand gestures as compared to the other existing methods with robust hand gesture recognition and corresponding emotion expressions, in real time.

• 한국정보기술학회 영문논문지
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• 제8권2호
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• pp.79-87
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• 2018

The current PC user authentication uses character password based on user's knowledge. However, this can easily be exploited by password cracking or key-logging programs. In addition, the use of a difficult password and the periodic change of the password make it easy for the user to mistake exposing the password around the PC because it is difficult for the user to remember the password. In order to overcome this, we propose user gesture recognition and challenge-response authentication. We apply user's hand gesture instead of character password. In the challenge-response method, authentication is performed in the form of responding to a quiz, rather than using the same password every time. To apply the hand gesture to challenge-response authentication, the gesture is recognized and symbolized to be used in the quiz response. So we show that this method can be applied to PC user authentication.

• 경영과정보연구
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• 제4권
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• pp.395-407
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• 2000

It is necessary to develop method that human and computer can interfact by the hand gesture without any special device. In this thesis, the real time hand gesture recognition was developed. The system segments the region of a hand recognizes the hand posture and track the movement of the hand, using computer vision. And it does not use the blue screen as a background, the data glove and special markers for the recognition of the hand gesture.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2012년도 춘계학술발표대회
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• pp.436-439
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• 2012

The work is to the control the desktop Computers based on hand gesture recognition. This paper is worked en real time tracking and recognizes the hand gesture for controlling the slides based on hand direction such as right and left using a real time camera.

• 한국멀티미디어학회논문지
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• 제20권8호
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• pp.1187-1199
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• 2017

In recent years, research about Natural User Interface (NUI) has become focused because NUI system can give natural feelings for users in virtual reality. Most important thing in NUI system is how to communicate with the computer system. There are many things to interact with users such as speech, hand gestures, body actions. Among them, hand gesture is suitable for the purpose of NUI because people often use a relatively high frequency in daily life and hand gesture have meaning only by itself. This hand gestures called multi-cultural hand gesture and we proposed the method to recognize this kind of hand gestures. Proposed method is composed of Histogram of Oriented Gradients (HOG) used for hand shape recognition and Histogram of Oriented Displacements (HOD) used for hand center point trajectory recognition.

• IEIE Transactions on Smart Processing and Computing
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• 제1권1호
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• pp.1-7
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• 2012

This paper presents a system used to automatically recognize the road traffic control gestures of police officers. In this approach,the control gestures of traffic police officers are captured in the form of depth images.A human skeleton is then constructed using a kinematic model. The feature vector describing a traffic control gesture is built from the relative angles found amongst the joints of the constructed human skeleton. We utilize Support Vector Machines (SVMs) to perform the gesture recognition. Experiments show that our proposed method is robust and efficient and is suitable for real-time application. We also present a testbed system based on the SVMs trained data for real-time traffic gesture recognition.

• 스마트미디어저널
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• 제8권3호
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• pp.47-52
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• 2019

In this paper, we designed HW / SW interfaces for processing the signals of capacitive sensors like Electric Potential Sensor (EPS) to detect the surrounding electric field disturbance as feature signals in motion recognition systems. We implemented a smart light control system with those interfaces. In the system, the on/off switch and brightness adjustment are controlled by hand gestures using the designed and fabricated interface circuits. PWM (Pulse Width Modulation) signals of the controller with a driver IC are used to drive the LED and to control the brightness and on/off operation. Using the hand-gesture signals obtained through EPS sensors and the interface HW/SW, we can not only construct a gesture instructing system but also accomplish the faster recognition speed by developing dedicated interface hardware including control circuitry. Finally, using the proposed hand-gesture recognition and signal processing methods, the light control module was also designed and implemented. The experimental result shows that the smart light control system can control the LED module properly by accurate motion detection and gesture classification.

• 제어로봇시스템학회논문지
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• 제8권7호
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• pp.599-606
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• 2002

A new method to govern the navigation of a mobile robot using hand gesture recognition is proposed based on the following two procedures. One is to achieve vision information by using a 2-DOF camera as a communicating medium between a man and a mobile robot and the other is to analyze and to control the mobile robot according to the recognized hand gesture commands. In the previous researches, mobile robots are passively to move through landmarks, beacons, etc. In this paper, to incorporate various changes of situation, a new control system that manages the dynamical navigation of mobile robot is proposed. Moreover, without any generally used expensive equipments or complex algorithms for hand gesture recognition, a reliable hand gesture recognition system is efficiently implemented to convey the human commands to the mobile robot with a few constraints.