• Title, Summary, Keyword: 손 동작 인식

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Advanced Representation Method of Hand Motion by Cheremes Analysis in KSL (수화소 분석을 통한 손동작 움직임 표현방법)

  • Lee, Boo-Hyung;Song, Pi1-Jae
    • Journal of Korea Multimedia Society
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    • v.9 no.8
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    • pp.1067-1075
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    • 2006
  • This paper proposes a advanced representation method of hand motion by cheremes analysis in korean sign language. The proposed method is the representation method which apply to the hand motion used in KSL(Korean Sign Language) to represent rich and united hand motion. Words or sentences in KSL are completed by combination of elements called as Cheremes, that is, a hand movement orientation, a finger shape, a hand position, etc. In this paper, Cheremes composing the KSL is divided and represented by 5 elements: the hand movement orientation(HMO), finger shape(FS), hand orientation(HO), hand position(HP) and number of using hand (HN). Each cheremes is expressed by more various characteristics. For example, The hand movement orientation means orientations which the hand move while the sign language is done and can be expressed by 17orientation components. The finger shape means various shapes which fingers can take and represented by 17 components. The Orientation of hand is expressed by 2 characteristics according to whether we use the palm of the hand or the back. The position of hand means specific regions in body which hand(s) is placed while the sign language is done and divided by 8 regions. Finally, the number of hand means whether use only one hand or both hands and is expressed by 2 characteristics. The proposed method has been tested with KSL words and sentences and the results have shown that they can be expressed completely by the proposed representation method.

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On-line Motion Control of Avatar Using Hand Gesture Recognition (손 제스터 인식을 이용한 실시간 아바타 자세 제어)

  • Kim, Jong-Sung;Kim, Jung-Bae;Song, Kyung-Joon;Min, Byung-Eui;Bien, Zeung-Nam
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.36C no.6
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    • pp.52-62
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    • 1999
  • This paper presents a system which recognizes dynamic hand gestures on-line for controlling motion of numan avatar in virtual environment(VF). A dynamic hand gesture is a method of communication between a computer and a human being who uses gestures, especially both hands and fingers. A human avatar consists of 32 degree of freedom(DOF) for natural motion in VE and navigates by 8 pre-defined dynamic hand gestures. Inverse kinematics and dynamic kinematics are applied for real-time motion control of human avatar. In this paper, we apply a fuzzy min-max neural network and feature analysis method using fuzzy logic for on-line dynamic hand gesture recognition.

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A Sign Language Translator using Data Mining in Kinect Environment (키넥트 환경에서 데이터 마이닝을 이용한 수화 번역기)

  • Lee, Sang-Jun;Woo, Tea-Ho;Kim, Jia;Park, Seon-Yeong;Lee, Soo-Won;Kim, Gye-Young
    • Proceedings of the Korea Information Processing Society Conference
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    • pp.619-622
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    • 2012
  • 본 연구에서는 키넥트(Kinect) 센서를 통해 수화 동작에서 손의 좌표와 이동방향을 추출하여 속성으로 하고, 데이터 마이닝의 분류 기법을 통해 수화를 인식하여 그 결과를 한글 텍스트로 번역해주는 소프트웨어를 개발한다. 제안 방법의 1단계에서는 0.05초 단위로 추출한 손의 좌표만을 속성으로 한다. 2단계에서는 개개인의 특성 및 화면상의 위치와 같은 요소에 따라 좌표 값이 달라지기 때문에, 손의 움직임에서 변위를 추출하여 손이 움직이는 방향을 속성으로 한다. 하지만 비슷한 방향으로 움직이는 수화가 있을 경우 수화의 구분이 어려우므로 3단계에서는 손의 좌표, 방향 두 가지를 분류하는 속성으로 사용한다. 향후 연구 방향은 수화의 중요한 요소인 손의 위치를 속성으로 추가시키고, 데이터 마이닝의 부스팅(Boosting) 기법을 적용하여 인식률을 높이는 것이다.

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The Study on Dynamic Images Processing for Finger Languages (지화 인식을 위한 동영상 처리에 관한 연구)

  • Kang, Min-Ji;Choi, Eun-Sook;Sohn, Young-Sun
    • Journal of Korean Institute of Intelligent Systems
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    • v.14 no.2
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    • pp.184-189
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    • 2004
  • In this paper, we realized a system that receives the dynamic images of finger languages, which is the method of intention transmission of the hearing disabled person, using the white and black CCD camera, and that recognizes the images and converts them to the editable text document. We use the afterimage to draw a sharp line between indistinct images and clear images from a series of inputted images, and get the character alphabet from the away of continuous images and output the accomplished character to the word editor by applying the automata theory. After the system removes the varied wrist part from the data of clean image, it gets the controid point of hand by the maximum circular movement method and recognizes the hand that is necessary to analyze the finger languages by applying the circular pattern vector algorithm. The system abstracts the characteristic vectors of the hand using the distance spectrum from the center of the hand and it compares the characteristic vector of inputted pattern from the standard pattern by applying the fuzzy inference and recognizes the movement of finger languages.

Hand Gesture Detection based on Motion History Tracking (운동 축적 트랙킹 기반 손 동작 인식)

  • Kim, Mina;Kim, Manbae
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • pp.146-147
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    • 2016
  • 손동작 인식은 대부분 스킨 컬러 검출을 이용하였다. 하지만 이와 같은 방법으로는 빛이나 주변 사물에 의해 영향을 많이 받기 때문에 정확한 값을 일정하게 도출 해낼 수 없었다. 이에 본 논문은 운동축적 기법을 이용하여 움직임을 파악한 후 손의 움직임을 트랙킹하여 운동 방향을 구한다. 제안된 시스템은 C/C++을 기반으로 구현하여, 실험에서 제안 방법이 안정적이고 우수한 성능을 보여줌을 증명하였다.

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Implementation of Real-time Recognition System for Continuous Korean Sign Language(KSL) mixed with Korean Manual Alphabet(KMA) (지문자를 포함한 연속된 한글 수화의 실시간 인식 시스템 구현)

  • Lee, Chan-Su;Kim, Jong-Sung;Park, Gyu-Tae;Jang, Won;Bien, Zeung-Nam
    • Journal of the Korean Institute of Telematics and Electronics C
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    • v.35C no.6
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    • pp.76-87
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    • 1998
  • This paper deals with a system which recognizes dynmic hand gestures, Korean Sign Language(KSL), mixed with static hand gesture, Korean Manual Alphabet(KMA), continuously. Recognition of continuous hand gestures is very difficult for lack of explicit tokens indicating beginning and ending of signs and for complexity of each gesture. In this paper, state automata is used for segmenting sequential signs into individual ones, and basic elements of KSL and KMA, which consist of 14 hand directions, 23 hand postures and 14 hand orientations are used for recognition of complex gestures under consideration of expandability. Using a pair of CyberGlove and Polhemus sensor, this system recognizes 131 Korean signs and 31 KMA's in real-time with recognition rate 94.3% for KSL excluding no recognition case and 96.7% for KMA.

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The Control of Avatar Motion using Hand Gestures (손 제스처를 이용한 아바타 동작 제어)

  • 이찬수;김상원;박찬종
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • pp.124-129
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    • 1998
  • 제스처는 사람들의 의사전달의 자연스러운 수단으로 컴퓨터와 사람의 자연스러운 인터페이슬를 제공할 수 있다. 본 연구에서는 적절한 움직임을 생성하기 위한 명령을 내리기 위하여 손제스터 인식 시스템을 이용하였다. 가상환경에서 아바타의 10가지 기본 동작을 생성하기 위해서 16가지의 제스처를 정의하고, 이 제스처의 인식에 의한 아바타의 움직임을 생성한다.

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Gender Recognition of Human Behavior with Neural Network Classifier (인공 신경망 분류기를 이용한 인간 행동의 성별 인식)

  • 류중원;조성배
    • Proceedings of the Korean Information Science Society Conference
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    • pp.140-142
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    • 2000
  • 인간과 기계가 효과적인 상호작용을 하기 위해서는 컴퓨터 시스템이 인간의 행동을 인식할 수 있어야 한다. 본 연구에서는 인공 신경망을 사용하여 컴퓨터 시스템이 인간의 움직임을 관찰한 후 행위자의 성별을 인식하도록 하는 시스템을 구현하였다. 두 가지 감정상태(보통상태, 화난 상태) 하에서 일어난 인간의 세 가지 동작(문 두드리기, 손 흔들기, 물건 들어올리기)을 대상으로 하여 인간 동작 데이터를 통해 만들어진 학습 데이터를 통해 98.0%의 인식률을 보일 때까지 학습시키고 나서, 이전에 사용하지 않았던 새로운 데이터에 대해 얼마나 설별을 잘 구별해 내는지 실험하였다. 동작이 일어나는 동안 행위자의 몸 여섯 군데에서 속도 데이터를 얻어내서 신경망의 입력값으로 사용하였다. 그 결과 최저 62.3%이상 최고 94.3%까지 인간 성별을 구분해 낼 수 있었고 이는 같은 데이터에 대해서 사람을 통해 실험한 것보다 훨씬 나은 것이다.

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Recognition of Conducting Motion using HMM (HMM을 이용한 지휘 동작의 인식)

  • 문형득;구자영
    • Journal of the Korea Society of Computer and Information
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    • v.9 no.1
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    • pp.25-30
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    • 2004
  • In this Paper, a beat recognition method from a sequence of images of conducting person was proposed. Hand position was detected using color discrimination, and symbolized by quantization. Then a motion of the conductor was represented as a sequence of symbols. HMM (Hidden Markov Model), which is excellent for recognition of sequence pattern with some level of variation, was used to recognize the sequence of symbols to be a motion for a beat.

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Hand gesture based a pet robot control (손 제스처 기반의 애완용 로봇 제어)

  • Park, Se-Hyun;Kim, Tae-Ui;Kwon, Kyung-Su
    • Journal of the Korea Industrial Information Systems Research
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    • v.13 no.4
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    • pp.145-154
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    • 2008
  • In this paper, we propose the pet robot control system using hand gesture recognition in image sequences acquired from a camera affixed to the pet robot. The proposed system consists of 4 steps; hand detection, feature extraction, gesture recognition and robot control. The hand region is first detected from the input images using the skin color model in HSI color space and connected component analysis. Next, the hand shape and motion features from the image sequences are extracted. Then we consider the hand shape for classification of meaning gestures. Thereafter the hand gesture is recognized by using HMMs (hidden markov models) which have the input as the quantized symbol sequence by the hand motion. Finally the pet robot is controlled by a order corresponding to the recognized hand gesture. We defined four commands of sit down, stand up, lie flat and shake hands for control of pet robot. And we show that user is able to control of pet robot through proposed system in the experiment.

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