• Title, Summary, Keyword: 손 추적

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Design of Computer Vision Interface by Recognizing Hand Motion (손동작 인식에 의한 컴퓨터 비전 인터페이스 설계)

  • Yun, Jin-Hyun;Lee, Chong-Ho
    • Journal of the Institute of Electronics Engineers of Korea CI
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    • v.47 no.3
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    • pp.1-10
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    • 2010
  • As various interfacing devices for computational machines are being developed, a new HCI method using hand motion input is introduced. This interface method is a vision-based approach using a single camera for detecting and tracking hand movements. In the previous researches, only a skin color is used for detecting and tracking hand location. However, in our design, skin color and shape information are collectively considered. Consequently, detection ability of a hand increased. we proposed primary orientation edge descriptor for getting an edge information. This method uses only one hand model. Therefore, we do not need training processing time. This system consists of a detecting part and a tracking part for efficient processing. In tracking part, the system is quite robust on the orientation of the hand. The system is applied to recognize a hand written number in script style using DNAC algorithm. Performance of the proposed algorithm reaches 82% recognition ratio in detecting hand region and 90% in recognizing a written number in script style.

Real-Time Hand Pose Tracking and Finger Action Recognition Based on 3D Hand Modeling (3차원 손 모델링 기반의 실시간 손 포즈 추적 및 손가락 동작 인식)

  • Suk, Heung-Il;Lee, Ji-Hong;Lee, Seong-Whan
    • Journal of KIISE:Software and Applications
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    • v.35 no.12
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    • pp.780-788
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    • 2008
  • Modeling hand poses and tracking its movement are one of the challenging problems in computer vision. There are two typical approaches for the reconstruction of hand poses in 3D, depending on the number of cameras from which images are captured. One is to capture images from multiple cameras or a stereo camera. The other is to capture images from a single camera. The former approach is relatively limited, because of the environmental constraints for setting up multiple cameras. In this paper we propose a method of reconstructing 3D hand poses from a 2D input image sequence captured from a single camera by means of Belief Propagation in a graphical model and recognizing a finger clicking motion using a hidden Markov model. We define a graphical model with hidden nodes representing joints of a hand, and observable nodes with the features extracted from a 2D input image sequence. To track hand poses in 3D, we use a Belief Propagation algorithm, which provides a robust and unified framework for inference in a graphical model. From the estimated 3D hand pose we extract the information for each finger's motion, which is then fed into a hidden Markov model. To recognize natural finger actions, we consider the movements of all the fingers to recognize a single finger's action. We applied the proposed method to a virtual keypad system and the result showed a high recognition rate of 94.66% with 300 test data.

A Study on Hand Gesture Recognition with Low-Resolution Hand Images (저해상도 손 제스처 영상 인식에 대한 연구)

  • Ahn, Jung-Ho
    • Journal of Satellite, Information and Communications
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    • v.9 no.1
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    • pp.57-64
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    • 2014
  • Recently, many human-friendly communication methods have been studied for human-machine interface(HMI) without using any physical devices. One of them is the vision-based gesture recognition that this paper deals with. In this paper, we define some gestures for interaction with objects in a predefined virtual world, and propose an efficient method to recognize them. For preprocessing, we detect and track the both hands, and extract their silhouettes from the low-resolution hand images captured by a webcam. We modeled skin color by two Gaussian distributions in RGB color space and use blob-matching method to detect and track the hands. Applying the foodfill algorithm we extracted hand silhouettes and recognize the hand shapes of Thumb-Up, Palm and Cross by detecting and analyzing their modes. Then, with analyzing the context of hand movement, we recognized five predefined one-hand or both-hand gestures. Assuming that one main user shows up for accurate hand detection, the proposed gesture recognition method has been proved its efficiency and accuracy in many real-time demos.

Hand detection using depth information (깊이 정보를 이용한 손 검출 방법)

  • Park, Sangheon;Kim, Joongrock;Kim, Jaesung;Lee, Sangyoun
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • pp.299-300
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    • 2011
  • 최근 손 동작 인식은 새로운 맨머신인터페이스(man-machine interface)를 위한 기술로 주목 받고 있으며, 이를 위한 손 검출은 손 동작 인식이나 손 추적을 위해 반드시 선행되어야 하는 중요한 기술이다. 기존에 연구되어온 대부분의 손 검출 방법으로는 색상을 기반으로 한 손 검출이었다. 하지만 색상을 기반으로 한 손 검출은 조명의 영향을 많이 받아 신뢰성을 보장하기 어렵다. 이러한 조명의 영향은 깊이 정보(depth information)를 이용함으로써 조명 변화에 강인한 손 검출을 수행할 수 있다. 본 논문에서는 손 검출을 깊이 정보를 활용하여 수행할 수 있는 방법을 제안하였다. 실시간으로 깊이 정보를 생성할 수 있는 depth sensor 하나를 사용하여 깊이 영상을 얻고 노이즈를 개선 해 준 후에 정의된 모션을 사용하여 손의 특징을 추출하여 손 검출을 하였다.

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A real-time robust body-part tracking system for intelligent environment (지능형 환경을 위한 실시간 신체 부위 추적 시스템 -조명 및 복장 변화에 강인한 신체 부위 추적 시스템-)

  • Jung, Jin-Ki;Cho, Kyu-Sung;Choi, Jin;Yang, Hyun S.
    • 한국HCI학회:학술대회논문집
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    • pp.411-417
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    • 2009
  • We proposed a robust body part tracking system for intelligent environment that will not limit freedom of users. Unlike any previous gesture recognizer, we upgraded the generality of the system by creating the ability the ability to recognize details, such as, the ability to detect the difference between long sleeves and short sleeves. For the precise each body part tracking, we obtained the image of hands, head, and feet separately from a single camera, and when detecting each body part, we separately chose the appropriate feature for certain parts. Using a calibrated camera, we transferred 2D detected body parts into the 3D posture. In the experimentation, this system showed advanced hand tracking performance in real time(50fps).

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The Center of Hand Detection Using Geometric feature of Hand Image (손 이미지의 기하학적 특징을 이용한 중심 검출)

  • Kim, Min-Ha;Lee, Sang-Geol;Cho, Jae-Hyun;Cha, Eui-Young
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.311-313
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    • 2012
  • 본 논문에서는 RGBD(Red Green Blue Depth)센서를 이용하여 얻은 영상의 깊이 정보와 손 이미지의 기하학적 특징을 이용하여 손의 중심을 검출하는 방법을 제안한다. 영상의 깊이 정보와 피부색 정보를 이용하여 손 영역을 검출한다. 검출된 손의 기하학적 정보로 손에 대한 볼록 외피(convex hull)를 형성한다. 볼록 외피의 정점들(vertices)의 위치 정보를 이용하여 손의 중심을 찾는다. 손의 중심은 손의 위치를 추적하거나 손가락 개수를 구하는 것 등에 이용될 수 있다. 이러한 응용은 인간과 컴퓨터의 상호작용(HCI, Human Computer Interface)을 이용한 시스템에 적용될 수 있다.

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Recognition of Finger Language Using FCM Algorithm (FCM 알고리즘을 이용한 지화 인식)

  • Kim, Kwang-Baek;Woo, Young-Woon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.6
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    • pp.1101-1106
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    • 2008
  • People who have hearing difficulties suffer from satisfactory mutual interaction with normal people because there are little chances of communicating each other. It is caused by rare communication of people who have hearing difficulties with normal people because majority of normal people can not understand sing language that is represented by gestures and is used by people who have hearing difficulties as a principal way of communication. In this paper, we propose a recognition method of finger language using FCM algorithm in order to be possible of communication of people who have hearing difficulties with normal people. In the proposed method, skin regions are extracted from images acquired by a camera using YCbCr and HSI color spaces and then locations of two hands are traced by applying 4-directional edge tracking algorithm on the extracted skin lesions. Final hand regions are extracted from the traced hand regions by noise removal using morphological information. The extracted final hand regions are classified and recognized by FCM algorithm. In the experiment using images of finger language acquired by a camera, we verified that the proposed method have the effect of extracting two hand regions and recognizing finger language.

Hand Tracking based on CamShift using Motion History Image (운동 히스토리 영상을 활용한 CamShift 기반 손 추적 기법)

  • Gil, Jong In;Kim, Mina;Whang, Whankyu;Kim, Manbae
    • Journal of Broadcast Engineering
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    • v.22 no.2
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    • pp.182-192
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    • 2017
  • In this paper, we propose hand tracking system combined with color and motion information. Most of hand detection and tracking systems are performed by modeling skin color. However, in this approach, since it is highly influenced by light or surrounding objects, accurate values cannot be derived constantly. Also, depending on the skin color, hand tracking may be interrupted by not only the hand but also the background with a color similar to that of the face and skin. Therefore, we design the hand tracking that can effectively track a hand by using motion history image(MHI) and combining it with CamShift. The proposed system is implemented based on C/C++, and the experiments proved that the proposed method shows stable and excellent performance.

Tracking Algorithm For Golf Swing Using the Information of Pixels and Movements (화소 및 이동 정보를 이용한 골프 스윙 궤도 추적 알고리즘)

  • Lee, Hong, Ro;Hwang, Chi-Jung
    • The KIPS Transactions:PartB
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    • v.12B no.5
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    • pp.561-566
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    • 2005
  • This paper presents a visual tracking algorithm for the golf swing motion analysis by using the information of the pixels of video frames and movement of the golf club to solve the problem fixed center point in model based tracking method. The model based tracking method use the polynomial function for trajectory displaying of upswing and downswing. Therefore it is under the hypothesis of the no movement of the center of gravity so this method is not for the amateurs. we proposed method using the information of pixel and movement, we first detected the motion by using the information of pixel in the frames in golf swing motion. Then we extracted the club head and hand by a properties of club shaft that consist of the parallel line and the moved location of club in up-swing and down-swing. In addition, we can extract the center point of user by tracking center point of the line between center of head and both foots. And we made an experiment with data that movement of center point is big. Finally, we can track the real trajectory of club head, hand and center point by using proposed tracking algorithm.

Hand Detection Using Motion Detection and Skin Detection (동작 검출과 피부색 검출을 이용한 손 검출)

  • Lee, Sang-Hyup;Son, Geum-Yeong;Kim, Sang-Min;Kim, Hyun-Tae
    • Proceedings of the Korean Society of Computer Information Conference
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    • pp.297-298
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    • 2016
  • 본 논문에서는 손을 보다 효과적으로 인식하기 위해 동작 검출과 피부색 검출을 이용하여 인식하는 시스템을 제안한다. 단순히 피부색만을 이용하여 손을 인식하는 경우 피부색과 유사한 색상의 물체나 다른 신체 부위를 인식하는 문제점이 발생하게 된다. 이러한 문제점을 해결하기 위해 동작 검출을 이용하여 움직이는 물체만을 손이라고 가정하였다. 이렇게 가정을 하고 피부색 검출과 동작 검출을 이용하여 인식하는 경우 신체부위를 제외하고는 거의 검출되지 않는다. 그리고 인식된 영역마다 뼈대를 찾아 손을 검출한다. 조명이나 주변 환경에 최대한 영향을 적게 받기위해 시스템을 설계하였으며 단순 피부색 검출을 이용한 손 검출보다 좋은 성능을 발휘하며 손가락의 개수와 손 모양, 손 추적까지 응용할 수 있다.

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