• Journal of Internet Computing and Services
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• v.17 no.2
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• pp.29-37
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• 2016

Humans develop and maintain relationship through communication. Communication is largely divided into verbal communication and non-verbal communication. Verbal communication involves the use of a language or characters, while non-verbal communication utilizes body language. We use gestures with language together in conversations of everyday life. Gestures belong to non-verbal communication, and can be offered using a variety of shapes and movements to deliver an opinion. For this reason, gestures are spotlighted as a means of implementing an NUI/NUX in the fields of HCI and HRI. In this paper, using Kinect and the geometric features of the hand, we propose a method for recognizing the number of fingers and detecting the hand area. A Kinect depth image can be used to detect the hand region, with the finger number identified by comparing the distance of outline and the central point of a hand. Average recognition rate for recognizing the number of fingers is 98.5%, from the proposed method, The proposed method would help enhancing the functionality of the human computer interaction by increasing the expression range of gestures.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.3
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• pp.535-540
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• 2007

The hand recognition technique is widely used to the economic input method for user interfacing environment. However, the most of the techniques have the restricted with recognize that only a fixed background and a regular pattern. This restriction character has brought a difficult problem to apply at variable application class and to process restriction environment. In this paper, we propose a virtual input system that extracting about hand region information that is not restricted by background image and also that can be followed the location information. This research could be used some system demanded by input of a person such as control system at airport and pavilion and economic virtual input system in class of industrial computer and various kinds control-system.

• Smart Media Journal
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• v.5 no.3
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• pp.25-29
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• 2016

This paper presents research for non-contact gesture recognition system using EPS(Electronic Potential Sensor) for measuring the human body of electromagnetic fields. It implemented a signal acquisition and signal processing system for designing a system suitable for motion recognition using the data coming from the sensors. we transform AC-type data into DC-type data by applying a 10Hz LPF considering H/W sampling rate. in addition, we extract 2-dimensional movement information by taking difference value between two cross-diagonal deployed sensor.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.3
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• pp.1-11
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• 2017

There is a Growing Interest in Motion Recognition for Recognizing Human Motion in Camera Images. As a Result, Researches are Being Actively Conducted to Control Digital Devices with Gestures at a Long Distance. The Interface Using Gesture can be Effectively Used in the Digital Signage Industry Where the Advertisement Effect is Expected to be Exposed to the Public in Various Places. Since the Digital Signage Contents can be Easily Controlled through the Non-contact Hand Operation, it is Possible to Provide the Advertisement Information of Interest to a Large Number of People, Thereby Providing an Opportunity to Lead to Sales. Therefore, we Propose a Digital Signage Content Control System Based on Hand Movement at a Certain Distance, which can be Effectively Used for the Development of Interactive Advertizing Media.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.37-43
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• 2023

The hospital situation, timing, and patient restrictions have become obstacles to an optimum therapy session. The crowdedness of the hospital might lead to a tight schedule and a shorter period of therapy. This condition might strike a post-stroke patient in a dilemma where they need regular treatment to recover their nervous system. In this work, we propose an in-house and uncomplex serious game system that can be used for physical therapy. The Kinect camera is used to capture the depth image stream of a human skeleton. Afterwards, the user might use their hand gesture to control the game. Voice recognition is deployed to ease them with play. Users must complete the given challenge to obtain a more significant outcome from this therapy system. Subjects will use their upper limb and hands to capture the 3D objects with different speeds and positions. The more substantial challenge, speed, and location will be increased and random. Each delegated entity will raise the scores. Afterwards, the scores will be further evaluated to correlate with therapy progress. Users are delighted with the system and eager to use it as their daily exercise. The experimental studies show a comparison between score and difficulty that represent characteristics of user and game. Users tend to quickly adapt to easy and medium levels, while high level requires better focus and proper synchronization between hand and eye to capture the 3D objects. The statistical analysis with a confidence rate(α:0.05) of the usability test shows that the proposed gaming is accessible, even without specialized training. It is not only for therapy but also for fitness because it can be used for body exercise. The result of the experiment is very satisfying. Most users enjoy and familiarize themselves quickly. The evaluation study demonstrates user satisfaction and perception during testing. Future work of the proposed serious game might involve haptic devices to stimulate their physical sensation.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.3
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• pp.210-216
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• 2015

It is well known that the structure of brain and consciousness of human have a phenomena of complex system. The human emotion have a many kind. The love is one of human emotion, which have been studied in sociology and psychology as a matter of great interested thing. In this paper, we consider a same and different time delay in love equation of Romeo and Juliet. We represent a behavior of love as a time series and phase portrait, and analyze the difference of behaviors between a same and different time delay.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.04a
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• pp.1081-1082
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• 2017

대부분의 동작 학습 시스템은 특정센서에 국한되어 있거나 동작인식에 불필요한 부위의 데이터까지 학습시켜 동작인식률에 영향을 끼친다. 이러한 문제점을 해결하기 위해 본 논문에서는 다양한 3D 센서에서 적용 가능한 동작 학습 및 인식 시스템을 제안한다. 또한 인체 운동학을 기반으로 동작에서 사용될 부위를 나누어 사용자가 선택하여 학습하게 한다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.4
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• pp.70-82
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• 1999

본 논문에서는 복잡한 영상에서 추출해낸 손 영역으로부터 제스처를 인식하여 인간과 컴퓨터의 상호작용(HCI, Human-Computer Interaction)을 위한 보다 자연스러운 인터페이스를 제공한다. 제안하는 방법은 정규화된 RGB 색상 공간에 정의한 피부색의 가우시안 분포를 이용해 조명의 변화나 개인의 차이에도 안정적으로 손 영역을 추출하며, 배경에 대한 상대적인 움직임을 이용해 복잡한 영상에서도 효과적으로 손 영역을 추출해 낸다. 추출된 손 영역은 RBF(Radial Basis Function) 신경망을 이용해 각 제스처로 인식된다. 가상 환경과의 상호작용을 제공하기 위해 두 종류의 기본적인 정적 제스처들을 정의하며 간단한 구문론적 규칙을 사용해 하나 이상의 인식 결과들을 조합함으로써 적은 수의 제스처들만으로 보다 효율적이고 다양한 상호작용이 가능하게 한다. 제안하는 시스템은 TM320C80 DSP 칩을 사용하여 구현되었으며 300×240 영상을 12Hz로 처리함으로써 빠른 속도로 가상 환경의 인터페이스를 제공한다.

• Proceedings of the Korean Information Science Society Conference
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• 2006.10b
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• pp.421-425
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• 2006

최근 들어서 휴머노이드 로봇을 비롯한 로봇에 대하여 관심이 증대되고 있다. 이에 따라, 외모를 닮은 로봇 뿐 만 아니라, 사람과 상호 작용을 할 수 있는 로봇 기술의 중요성이 부각되고 있다. 이러한 상호 작용을 위한 효율적이고, 가장 자연스러운 방법 중의 하나가 비전을 기반으로 한 제스처 인식이다. 제스처를 인식하는데 있어서 가장 중요한 것은 손의 모양과 움직임을 인식하는3차원 제스처 인식이다. 본 논문에서는 3차원 손 제스처를 인식하기 위하여3차원 손 모델 추정 방법과 명령형 제스처 인식 시스템을 소개하고, 수화, 지화 등으로의 확장성을 위한 프레임워크를 제안한다.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.10 no.3
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• pp.92-97
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• 2011

In this paper, a controller recognizing human gestures using EMG signal is shown. The tiny and band-type controller is developed for image training to excercise the specific area in the body, and uses a dry-type silver fiber electrode easy to be attached or detached itself to a skin. The captured EMG signals are converted to 10-bit digital values via amplification and frequency filtering processes within the controller, and are transmitted to the server by wireless. As the gesture recognition ratio using the proposed controller on biceps is up to 80%, we expect the practical potential of the controller is very promising.