• 제목/요약/키워드: Hand Detecting

검색결과 206건 처리시간 0.023초

깊이정보를 이용한 실시간 손 영역 검출 및 추적 (Real-time Hand Region Detection and Tracking using Depth Information)

  • 주성일;원선희;최형일
    • 정보처리학회논문지:소프트웨어 및 데이터공학
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    • 제1권3호
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    • pp.177-186
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    • 2012
  • 본 논문에서는 실시간 손동작 분석을 위한 깊이정보 기반 손 영역 검출 및 추적 방법을 제안한다. 이를 위해 손 영역 검출단계에서는 깊이정보만을 이용하여 손 영역의 특징인 형태모델을 생성하고, 검출 시 움직임 정보와 영역 확장(Region Growing)을 통해 객체를 추출한다. 추출된 객체는 사전에 생성된 형태모델과 크기정보를 분석하여 최종 손 영역으로 판정한다. 판정된 손 객체는 추적단계에서 중심점 전이 과정을 통해 이전 중심점과의 최근접점을 획득하고, 최근접점으로부터 영역 확장과 깊이기반 적응적 평균 이동 기법(DAM-Shift)을 통해 새로운 중심점을 검출하여 추적한다. 마지막으로 성능 검증을 위해 다양한 손 모양과 속도 및 위치에 대한 다양한 환경에서 실험하고, 검출속도와 추적된 궤적의 정량적, 정성적 분석을 통해 제안하는 방법의 효율성을 입증한다.

Hand Gesture Recognition using Optical Flow Field Segmentation and Boundary Complexity Comparison based on Hidden Markov Models

  • Park, Sang-Yun;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제14권4호
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    • pp.504-516
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    • 2011
  • In this paper, we will present a method to detect human hand and recognize hand gesture. For detecting the hand region, we use the feature of human skin color and hand feature (with boundary complexity) to detect the hand region from the input image; and use algorithm of optical flow to track the hand movement. Hand gesture recognition is composed of two parts: 1. Posture recognition and 2. Motion recognition, for describing the hand posture feature, we employ the Fourier descriptor method because it's rotation invariant. And we employ PCA method to extract the feature among gesture frames sequences. The HMM method will finally be used to recognize these feature to make a final decision of a hand gesture. Through the experiment, we can see that our proposed method can achieve 99% recognition rate at environment with simple background and no face region together, and reduce to 89.5% at the environment with complex background and with face region. These results can illustrate that the proposed algorithm can be applied as a production.

근전위 신호구동형 전동의수의 파지력 제어 (Grip Force Control of Myoelectric Signal Driving Type Myoelectric Hand Prosthesis)

  • 최기원;최규하;신우석
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2007년도 하계학술대회 논문집
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    • pp.340-342
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    • 2007
  • This paper presents the grip force control of myoelectric hand prosthesis according to myoelectric signal generated in the human muscle. The control system consist of a controller for driving DC motor, torque sensor for measuring out torque of motor, slip sensor for detecting slip of torque. The experimental results proved the reliability of proposed control system.

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주행 로봇을 위한 단일 카메라 영상에서 손든 자세 검출 알고리즘 (Hand Raising Pose Detection in the Images of a Single Camera for Mobile Robot)

  • 권기일
    • 로봇학회논문지
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    • 제10권4호
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    • pp.223-229
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    • 2015
  • This paper proposes a novel method for detection of hand raising poses from images acquired from a single camera attached to a mobile robot that navigates unknown dynamic environments. Due to unconstrained illumination, a high level of variance in human appearances and unpredictable backgrounds, detecting hand raising gestures from an image acquired from a camera attached to a mobile robot is very challenging. The proposed method first detects faces to determine the region of interest (ROI), and in this ROI, we detect hands by using a HOG-based hand detector. By using the color distribution of the face region, we evaluate each candidate in the detected hand region. To deal with cases of failure in face detection, we also use a HOG-based hand raising pose detector. Unlike other hand raising pose detector systems, we evaluate our algorithm with images acquired from the camera and images obtained from the Internet that contain unknown backgrounds and unconstrained illumination. The level of variance in hand raising poses in these images is very high. Our experiment results show that the proposed method robustly detects hand raising poses in complex backgrounds and unknown lighting conditions.

깊이 영상 기반 손 영역 추적 및 손 끝점 검출 (Hand Region Tracking and Fingertip Detection based on Depth Image)

  • 주성일;원선희;최형일
    • 한국컴퓨터정보학회논문지
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    • 제18권8호
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    • pp.65-75
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    • 2013
  • 본 논문에서는 깊이 영상만을 이용하여 손 영역 추적 및 손 끝점 검출 방법을 제안한다. 조명 조건의 영향을 제거하고 빠르고 안정적인 정보 획득을 위해 깊이 정보만을 이용하는 추적 방법을 제안하고, 영역 확장 방법을 통해 추적 과정 중에 발생할 수 있는 오류에 대한 판단 방법과 다양한 제스처 인식에 응용이 가능한 손 끝점 검출 방법을 제안한다. 먼저 추적점을 찾기 위해 중심점 전이 과정을 통해 최근접점을 찾고 그 점으로부터 영역 확장을 통해 손 영역과 경계선을 검출한다. 그리고 영역 확장을 통해 획득한 무효경계선의 비율을 이용하여 추적영역에 대한 신뢰도를 계산함으로써 정상 추적 여부를 판단한다. 정상적인 추적인 경우, 검출된 손 영역으로부터 윤곽선을 추출하고 곡률 및 RANSAC, 컨벡스 헐(Convex-Hull)을 이용하여 손 끝점을 검출한다. 마지막으로 성능 검증을 위해 다양한 상황에 따른 정량적, 정성적 분석을 통해 제안하는 추적 및 손 끝점 검출 알고리즘의 효율성을 입증한다.

A Study on Online Real-Time Strategy Game by using Hand Tracking in Augmented Reality

  • Jeon, Gwang-Ha;Um, Jang-Seok
    • 한국멀티미디어학회논문지
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    • 제12권12호
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    • pp.1761-1768
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    • 2009
  • In this paper, we implemented online real time strategy game using hand as the mouse in augmented reality. Also, we introduced the algorithm for detecting hand direction, finding fingertip of the index finger and counting the number of fingers for interaction between users and the virtual objects. The proposed method increases the reality of the game by combining the real world and the virtual objects. Retinex algorithm is used to remove the effect of illumination change. The implementation of the virtual reality in the online environment enables to extend the applicability of the proposed method to the areas such as online education, remote medical treatment, and mobile interactive games.

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AVHRR과 Landsat TM 자료를 이용한 적조 패취 관측 (Detection of Red Tide Patches using AVHRR and Landsat TM data)

  • 정종철
    • 환경영향평가
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    • 제10권1호
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    • pp.1-8
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    • 2001
  • Detection of red tides by satellite remote sensing can be done either by detecting enhanced level of chlorophyll pigment or by detecting changes in the spectral composition of pixels. Using chlorophyll concentration, however, is not effective currently due to the facts: 1) Chlorophyll-a is a universal pigment of phytoplankton, and 2) no accurate algorithm for chlorophyll in case 2 water is available yet. Here, red band algorithm, classification and PCA (Principal Component Analysis) techniques were applied for detecting patches of Cochlodinium polykrikoides red tides which occurred in Korean waters in 1995. This dinoflagellate species appears dark red due to the characteristic pigments absorbing lights in the blue and green wavelength most effectively. In the satellite image, the brightness of red tide pixels in all the three visible bands were low making the detection difficult. Red band algorithm is not good for detecting the red tide because of reflectance of suspended sediments. For supervised classification, selecting training area was difficult, while unsupervised classification was not effective in delineating the patches from surrounding pixels. On the other hand, PCA gave a good qualitative discrimination on the distribution compared with actual observation.

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Hand Tracking and Hand Gesture Recognition for Human Computer Interaction

  • Bai, Yu;Park, Sang-Yun;Kim, Yun-Sik;Jeong, In-Gab;Ok, Soo-Yol;Lee, Eung-Joo
    • 한국멀티미디어학회논문지
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    • 제14권2호
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    • pp.182-193
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    • 2011
  • The aim of this paper is to present the methodology for hand tracking and hand gesture recognition. The detected hand and gesture can be used to implement the non-contact mouse. We had developed a MP3 player using this technology controlling the computer instead of mouse. In this algorithm, we first do a pre-processing to every frame which including lighting compensation and background filtration to reducing the adverse impact on correctness of hand tracking and hand gesture recognition. Secondly, YCbCr skin-color likelihood algorithm is used to detecting the hand area. Then, we used Continuously Adaptive Mean Shift (CAMSHIFT) algorithm to tracking hand. As the formula-based region of interest is square, the hand is closer to rectangular. We have improved the formula of the search window to get a much suitable search window for hand. And then, Support Vector Machines (SVM) algorithm is used for hand gesture recognition. For training the system, we collected 1500 hand gesture pictures of 5 hand gestures. Finally we have performed extensive experiment on a Windows XP system to evaluate the efficiency of the proposed scheme. The hand tracking correct rate is 96% and the hand gestures average correct rate is 95%.

가이드라인을 이용한 동적 손동작 인식 (Dynamic Hand Gesture Recognition using Guide Lines)

  • 김건우;이원주;전창호
    • 전자공학회논문지CI
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    • 제47권5호
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    • pp.1-9
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    • 2010
  • 일반적으로 동적 손동작 인식을 위해서는 전처리, 손 추적, 손 모양 검출의 단계가 필요하다. 본 논문에서는 전처리와 손 모양 검출 방법을 개선함으로써 성능을 향상시킨 동적 손동작 인식 방법을 제안한다. 전처리 단계에서는 동적테이블을 이용하여 노이즈제거 성능을 높이고, YCbCr 컬러공간을 이용한 기존의 피부색 검출 방식에서 피부색의 범위를 조절할 수 있도록 하여 피부색 검출 성능을 높인다. 특히 손 모양 검출 단계에서는 가이드라인을 이용하여 동적 손동작 인식의 요소인 시작이미지(Start Image)와 정지 이미지(Stop Image)를 검출하여 동적 손동작을 인식하기 때문에 학습예제를 사용한 손동작 인식 방법에 비해 인식 속도가 빠르다는 이점이 있다. 가이드라인이란 웹캠을 통해 입력되는 손의 모양과 비교하여 검출하기 위해 화면에 출력하는 손 모양의 라인이다. 가이드라인을 이용한 동적 손동작 인식 방법의 성능을 평가하기 위해 웹캠을 사용하여 복잡한 배경과 단순한 배경으로 구분된 9가지 동영상을 대상으로 실험하였다. 그 결과 CPU 점유율이 낮고, 메모리 사용량도 적기 때문에 시스템 부하가 높은 환경에 효과적임을 알 수 있었다.

한글 수화용 동적 손 제스처의 실시간 인식 시스템의 구현에 관한 연구 (On-line dynamic hand gesture recognition system for the korean sign language (KSL))

  • 김종성;이찬수;장원;변증남
    • 전자공학회논문지C
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    • 제34C권2호
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    • pp.61-70
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    • 1997
  • Human-hand gestures have been used a means of communication among people for a long time, being interpreted as streams of tokens for a language. The signed language is a method of communication for hearing impaired person. Articulated gestures and postures of hands and fingers are commonly used for the signed language. This paper presents a system which recognizes the korean sign language (KSL) and translates the recognition results into a normal korean text and sound. A pair of data-gloves are used a sthe sensing device for detecting motions of hands and fingers. In this paper, we propose a dynamic gesture recognition mehtod by employing a fuzzy feature analysis method for efficient classification of hand motions, and applying a fuzzy min-max neural network to on-line pattern recognition.

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