• Title, Summary, Keyword: hand gesture recognition

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Gesture Recognition Algorithm by Analyzing Direction Change of Trajectory (궤적의 방향 변화 분석에 의한 제스처 인식 알고리듬)

  • Park Jahng-Hyon;Kim Minsoo
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.4
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    • pp.121-127
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    • 2005
  • There is a necessity for the communication between intelligent robots and human beings because of wide spread use of them. Gesture recognition is currently being studied in regards to better conversing. On the basis of previous research, however, the gesture recognition algorithms appear to require not only complicated algorisms but also separate training process for high recognition rates. This study suggests a gesture recognition algorithm based on computer vision system, which is relatively simple and more efficient in recognizing various human gestures. After tracing the hand gesture using a marker, direction changes of the gesture trajectory were analyzed to determine the simple gesture code that has minimal information to recognize. A map is developed to recognize the gestures that can be expressed with different gesture codes. Through the use of numerical and geometrical trajectory, the advantages and disadvantages of the suggested algorithm was determined.

Automation of an Interactive Interview System by Hand Gesture Recognition Using Particle Filter

  • Lee, Yang-Weon
    • Journal of information and communication convergence engineering
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    • v.9 no.6
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    • pp.633-636
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    • 2011
  • This paper describes a implementation of virtual interactive interview system. A hand motion recognition algorithm based on the particle filters is applied for this system. The particle filter is well operated for human hand motion recognition than any other recognition algorithm. Through the experiments, we show that the proposed scheme is stable and works well in virtual interview system's environments.

A new study on hand gesture recognition algorithm using leap motion system (Leap Motion 시스템을 이용한 손동작 인식기반 제어 인터페이스 기술 연구)

  • Nam, Jae-Hyun;Yang, Seung-Hun;Hu, Woong;Kim, Byung-Gyu
    • Journal of Korea Multimedia Society
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    • v.17 no.11
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    • pp.1263-1269
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    • 2014
  • As rapid development of new hardware control interface technology, new concepts have been being proposed and emerged. In this paper, a new approach based on leap motion system is proposed. While we employ a position information from sensor, the hand gesture recognition is suggested with the pre-defined patterns. To do this, we design a recognition algorithm with hand gesture and finger patterns. We apply the proposed scheme to 3-dimensional avatar controling and editing software tool for making animation in the cyber space as a representative application. This proposed algorithm can be used to control computer systems in medical treatment, game, education and other various areas.

Implement of Hand Gesture Interface using Ratio and Size Variation of Gesture Clipping Region (제스쳐 클리핑 영역 비율과 크기 변화를 이용한 손-동작 인터페이스 구현)

  • Choi, Chang-Yur;Lee, Woo-Beom
    • The Journal of The Institute of Internet, Broadcasting and Communication
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    • v.13 no.1
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    • pp.121-127
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    • 2013
  • A vision based hand-gesture interface method for substituting a pointing device is proposed in this paper, which is used the ratio and size variation of Gesture Region. Proposed method uses the skin hue&saturation of the hand region from the HSI color model to extract the hand region effectively. This method can remove the non-hand region, and reduces the noise effect by the light source. Also, as the computation quantity is reduced by detecting not the static hand-shape recognition, but the ratio and size variation of hand-moving from the clipped hand region in real time, more response speed is guaranteed. In order to evaluate the performance of the our proposed method, after applying to the computerized self visual acuity testing system as a pointing device. As a result, the proposed method showed the average 86% gesture recognition ratio and 87% coordinate moving recognition ratio.

Navigation of a Mobile Robot Using the Hand Gesture Recognition

  • Kim, Il-Myung;Kim, Wan-Cheol;Yun, Jae-Mu;Jin, Tae-Seok;Lee, Jang-Myung
    • 제어로봇시스템학회:학술대회논문집
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    • pp.126.3-126
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    • 2001
  • A new method to govern the navigation of a mobile robot is proposed based on the following two procedures: one is to achieve vision information by using a 2 D-O-F camera as a communicating medium between a man and a mobile robot and the other is to analyze and to behave according to the recognized hand gesture commands. In the previous researches, mobile robots are passively to move through landmarks, beacons, etc. To incorporate various changes of situation, a new control system manages the dynamical navigation of a mobile robot. 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.

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Hand Shape Classification using Contour Distribution (윤곽 분포를 이용한 이미지 기반의 손모양 인식 기술)

  • Lee, Changmin;Kim, DaeEun
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.6
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    • pp.593-598
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    • 2014
  • Hand gesture recognition based on vision is a challenging task in human-robot interaction. The sign language of finger spelling alphabets has been tested as a kind of hand gesture. In this paper, we test hand gesture recognition by detecting the contour shape and orientation of hand with visual image. The method has three stages, the first stage of finding hand component separated from the background image, the second stage of extracting the contour feature over the hand component and the last stage of comparing the feature with the reference features in the database. Here, finger spelling alphabets are used to verify the performance of our system and our method shows good performance to discriminate finger alphabets.

A Robust Fingertip Extraction and Extended CAMSHIFT based Hand Gesture Recognition for Natural Human-like Human-Robot Interaction (강인한 손가락 끝 추출과 확장된 CAMSHIFT 알고리즘을 이용한 자연스러운 Human-Robot Interaction을 위한 손동작 인식)

  • Lee, Lae-Kyoung;An, Su-Yong;Oh, Se-Young
    • Journal of Institute of Control, Robotics and Systems
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    • v.18 no.4
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    • pp.328-336
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    • 2012
  • In this paper, we propose a robust fingertip extraction and extended Continuously Adaptive Mean Shift (CAMSHIFT) based robust hand gesture recognition for natural human-like HRI (Human-Robot Interaction). Firstly, for efficient and rapid hand detection, the hand candidate regions are segmented by the combination with robust $YC_bC_r$ skin color model and haar-like features based adaboost. Using the extracted hand candidate regions, we estimate the palm region and fingertip position from distance transformation based voting and geometrical feature of hands. From the hand orientation and palm center position, we find the optimal fingertip position and its orientation. Then using extended CAMSHIFT, we reliably track the 2D hand gesture trajectory with extracted fingertip. Finally, we applied the conditional density propagation (CONDENSATION) to recognize the pre-defined temporal motion trajectories. Experimental results show that the proposed algorithm not only rapidly extracts the hand region with accurately extracted fingertip and its angle but also robustly tracks the hand under different illumination, size and rotation conditions. Using these results, we successfully recognize the multiple hand gestures.

A Hierarchical Bayesian Network for Real-Time Continuous Hand Gesture Recognition (연속적인 손 제스처의 실시간 인식을 위한 계층적 베이지안 네트워크)

  • Huh, Sung-Ju;Lee, Seong-Whan
    • Journal of KIISE:Software and Applications
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    • v.36 no.12
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    • pp.1028-1033
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    • 2009
  • This paper presents a real-time hand gesture recognition approach for controlling a computer. We define hand gestures as continuous hand postures and their movements for easy expression of various gestures and propose a Two-layered Bayesian Network (TBN) to recognize those gestures. The proposed method can compensate an incorrectly recognized hand posture and its location via the preceding and following information. In order to vertify the usefulness of the proposed method, we implemented a Virtual Mouse interface, the gesture-based interface of a physical mouse device. In experiments, the proposed method showed a recognition rate of 94.8% and 88.1% for a simple and cluttered background, respectively. This outperforms the previous HMM-based method, which had results of 92.4% and 83.3%, respectively, under the same conditions.

CNN-Based Hand Gesture Recognition for Wearable Applications (웨어러블 응용을 위한 CNN 기반 손 제스처 인식)

  • Moon, Hyeon-Chul;Yang, Anna;Kim, Jae-Gon
    • Journal of Broadcast Engineering
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    • v.23 no.2
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    • pp.246-252
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    • 2018
  • Hand gestures are attracting attention as a NUI (Natural User Interface) of wearable devices such as smart glasses. Recently, to support efficient media consumption in IoT (Internet of Things) and wearable environments, the standardization of IoMT (Internet of Media Things) is in the progress in MPEG. In IoMT, it is assumed that hand gesture detection and recognition are performed on a separate device, and thus provides an interoperable interface between these modules. Meanwhile, deep learning based hand gesture recognition techniques have been recently actively studied to improve the recognition performance. In this paper, we propose a method of hand gesture recognition based on CNN (Convolutional Neural Network) for various applications such as media consumption in wearable devices which is one of the use cases of IoMT. The proposed method detects hand contour from stereo images acquisitioned by smart glasses using depth information and color information, constructs data sets to learn CNN, and then recognizes gestures from input hand contour images. Experimental results show that the proposed method achieves the average 95% hand gesture recognition rate.

A Structure and Framework for Sign Language Interaction

  • Kim, Soyoung;Pan, Younghwan
    • Journal of the Ergonomics Society of Korea
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    • v.34 no.5
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    • pp.411-426
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    • 2015
  • Objective: The goal of this thesis is to design the interaction structure and framework of system to recognize sign language. Background: The sign language of meaningful individual gestures is combined to construct a sentence, so it is difficult to interpret and recognize the meaning of hand gesture for system, because of the sequence of continuous gestures. This being so, in order to interpret the meaning of individual gesture correctly, the interaction structure and framework are needed so that they can segment the indication of individual gesture. Method: We analyze 700 sign language words to structuralize the sign language gesture interaction. First of all, we analyze the transformational patterns of the hand gesture. Second, we analyze the movement of the transformational patterns of the hand gesture. Third, we analyze the type of other gestures except hands. Based on this, we design a framework for sign language interaction. Results: We elicited 8 patterns of hand gesture on the basis of the fact on whether the gesture has a change from starting point to ending point. And then, we analyzed the hand movement based on 3 elements: patterns of movement, direction, and whether hand movement is repeating or not. Moreover, we defined 11 movements of other gestures except hands and classified 8 types of interaction. The framework for sign language interaction, which was designed based on this mentioned above, applies to more than 700 individual gestures of the sign language, and can be classified as an individual gesture in spite of situation which has continuous gestures. Conclusion: This study has structuralized in 3 aspects defined to analyze the transformational patterns of the starting point and the ending point of hand shape, hand movement, and other gestures except hands for sign language interaction. Based on this, we designed the framework that can recognize the individual gestures and interpret the meaning more accurately, when meaningful individual gesture is input sequence of continuous gestures. Application: When we develop the system of sign language recognition, we can apply interaction framework to it. Structuralized gesture can be used for using database of sign language, inventing an automatic recognition system, and studying on the action gestures in other areas.