• Journal of Korea Multimedia Society
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• v.15 no.10
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• pp.1196-1204
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• 2012

In this paper, a series of algorithms are proposed for controlling different kinds of multimedia contents and realizing interact between human and computer by using single input device. Human gesture recognition based on NUI is presented firstly in my paper. Since the image information we get it from camera is not sensitive for further processing, we transform it to YCbCr color space, and then morphological processing algorithm is used to delete unuseful noise. Boundary Energy and depth information is extracted for hand detection. After we receive the image of hand detection, PCA algorithm is used to recognize hand posture, difference image and moment method are used to detect hand centroid and extract trajectory of hand movement. 8 direction codes are defined for quantifying gesture trajectory, so the symbol value will be affirmed. Furthermore, HMM algorithm is used for hand gesture recognition based on the symbol value. According to series of methods we presented, we can control multimedia contents by using human gesture recognition. Through large numbers of experiments, the algorithms we presented have satisfying performance, hand detection rate is up to 94.25%, gesture recognition rate exceed 92.6%, hand posture recognition rate can achieve 85.86%, and face detection rate is up to 89.58%. According to these experiment results, we can control many kinds of multimedia contents on computer effectively, such as video player, MP3, e-book and so on.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.12
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• pp.1100-1108
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• 2015

A camera-based real-time hand posture and gesture recognition system is proposed for controlling various devices inside automobiles. It uses an imaging system composed of a camera with a proper filter and an infrared lighting device to acquire images of hand-motion sequences. Several steps of pre-processing algorithms are applied, followed by a background normalization process before segmenting the hand from the background. The hand posture is determined by first separating the fingers from the main body of the hand and then by finding the relative position of the fingers from the center of the hand. The beginning and ending of the hand motion from the sequence of the acquired images are detected using pre-defined motion rules to start the hand gesture recognition. A set of carefully designed features is computed and extracted from the raw sequence and is fed into a decision tree-like decision rule for determining the hand gesture. Many experiments are performed to verify the system. In this paper, we show the performance results from tests on the 550 sequences of hand motion images collected from five different individuals to cover the variations among many users of the system in a real-time environment. Among them, 539 sequences are correctly recognized, showing a recognition rate of 98%.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.157-163
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• 2013

In this paper, we propose a vision and depth information based real-time hand gesture interface method using finger joint estimation. For this, the areas of left and right hands are segmented after mapping of the visual image and depth information image, and labeling and boundary noise removal is performed. Then, the centroid point and rotation angle of each hand area are calculated. Afterwards, a circle is expanded at following pattern from a centroid point of the hand to detect joint points and end points of the finger by obtaining the midway points of the hand boundary crossing and the hand model is recognized. Experimental results that our method enabled fingertip distinction and recognized various hand gestures fast and accurately. As a result of the experiment on various hand poses with the hidden fingers using both hands, the accuracy showed over 90% and the performance indicated over 25 fps. The proposed method can be used as a without contacts input interface in HCI control, education, and game applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.5
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• pp.1060-1065
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• 2011

In this paper, the proposed method is recognized the hands using color information with input image of the camera. It controls the mouse pointer using recognized hands. In addition, specific commands with the mouse pointer is designed to perform. Most users felt uncomfortable since existing interaction multimedia systems depend on a particular external input devices such as pens and mouse However, the proposed method is to compensate for these shortcomings by hand without the external input devices. In experimental methods, hand areas and backgrounds are separated using color information obtaining image from camera. And coordinates of the mouse pointer is determined using coordinates of the center of a separate hand. The mouse pointer is located in pre-filled area using these coordinates, and the robot will move and execute with the command. In experimental results, the recognition of the proposed method is more accurate but is still sensitive to the change of color of light.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.5
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• pp.619-628
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• 2010

Shape Memory Alloy (SMA) has recently received attention in developing implantable surgical equipments and it is expected to lead the future medical device market by adequately imitating surgeons' flexible and delicate hand movement. However, SMA actuators have not been used widely because of their nonlinear behavior called hysteresis, which makes their control difficult. Hence, we propose a parameter, $t_1$, which is necessary for temperature control, by analyzing the open-loop step response between current and temperature and by comparing it with the values of linear differential equations. $t_1$ is a pole of the transfer function in the invariant linear model in which the input and output are current and temperature, respectively; hence, $t_1$ is found to be related to the state variable used for temperature control. When considering the parameter under heat treatment conditions, $T_{max}$ was found to assume the lowest value, and $t_1$ was irrelevant to the heat treatment.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.233-237
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• 2005

수화의 인식 및 표현 기술에 대한 관련 연구는 수화 인식을 통한 건청인과의 의사 전달, 가상현실에서의 손동작 인식 등을 대상으로 여러 방면으로의 접근 및 연구 결과를 도출하고 있다. 그러나 이들 연구의 대부분 데스크탑 PC기반의 수신호(Hand signal) 제어 및 수화 - 손 동작 인식에 목적을 두었고 수화 신호의 획득을 위하여 영상장비를 이용하였으며 이를 바탕으로 단어 위주의 수화 인식 및 표현에 중점을 둔 수화 인식 시스템의 구현을 통해 비장애인과의 자유로운 의사소통을 추구하고 있다. 따라서 본 논문에서는 햅틱 장치로부터 사용자의 의미있는 수화 제스처를 획득하기 위한 접근 방식을 차세대 착용형 PC 플랫폼 기반의 유비쿼터스 환경으로 확대, 적용시켜 제스처 데이터 입력 모듈로부터 새로운 정보의 획득에 있어 한계성을 극복하고 사용자의 편의를 도모할 수 있는 효율적인 데이터 획득 방안을 제시한다. 또한 퍼지 알고리즘 및 RDBMS 모듈을 이용하여 언제, 어디에서나 사용자의 의미 있는 문장형 수화 제스처를 실시간으로 인식하고 표현하는 수화 제스처 인식기를 구현하였다. 본 논문에서는 수화 제스처 입력 모듈(5th Data Glove System과 $Fastrak{\circledR}$)과 차세대 착용형 PC 플랫폼(embedded I.MX21 board)간의 이격거리를 반경 10M의 타원 형태로 구성하고 규정된 위치로 수화 제스처 데이터 입력모듈을 이동시키면서 5인의 피실험자에 대하여 연속적으로 20회의 반복 실험을 수행하였으며 사용자의 동적 제스처 인식 실험결과 92.2% 평균 인식률을 도출하였다.

• Journal of Broadcast Engineering
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• v.14 no.3
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• pp.366-377
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• 2009

In this paper, we implement the real-time system which extracts 3-dimensional coordinates from right and left images captured by a stereo camera and provides users with reality through a virtual space operated by the 3-dimensional coordinates. In general, all pixels in correspondence region are compared for the disparity estimation. However, for a real time process, the central coordinates of the correspondence region are only used in the proposed algorithm. In the implemented system, 3D coordinates are obtained by using the depth information derived from the estimated disparity and we set user's hand as a region of interest(ROI). After user's hand is detected as the ROI, the system keeps tracking a hand's movement and generates a virtual space that is controled by the hand. Experimental results show that the implemented system could estimate the disparity in real -time and gave the mean-error less than 0.68cm within a range of distance, 1.5m. Also It had more than 90% accuracy in the hand recognition.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.851-859
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• 2002

This paper discusses the design of a working system that visually recognizes hand gestures for the control of a window based user interface. We present a method for tracking the fingertip of the index finger using a single camera. Our method is based on CAMSHIFT algorithm and performs better than the CAMSHIFT algorithm in that it tracks well particular hand poses used in the system in complex backgrounds. We describe how the location of the fingertip is mapped to a location on the monitor, and how it Is both necessary and possible to smooth the path of the fingertip location using a physical model of a mouse pointer. Our method is able to track in real time, yet not absorb a major share of computational resources. The performance of our system shows a great promise that we will be able to use this methodology to control computers in near future.

• Journal of Sensor Science and Technology
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• v.12 no.6
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• pp.289-297
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• 2003

In this paper, we propose accurate classification method of an EEG signals during a mental tasks. In the experimental task, subjects achieved through the process of responding to visual stimulus, understanding the given problem, controlling hand motions, and select a key. To recognize the subjects' selection time, we analyzed with 4 types feature from the filtered brain waves at frequency bands of $\alpha$, $\beta$, $\theta$, $\gamma$ waves. From the analysed features, we construct specific rules for each subject meta rules including common factors in all subjects. In this system, the architecture of the neural network is a three layered feedforward networks with one hidden layer which implements the error back propagation learning algorithm. Applying the algorithms to 4 subjects show 87% classification success rates. In this paper, the proposed detection method can be a basic technology for brain-computer-interface by combining with discrimination methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.5
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• pp.53-59
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• 2024

This study presents the design and implementation of a camera-based 6DoF (6 Degrees of Freedom) tracking and pose estimation system. In particular, we propose a method for accurately estimating the positions and orientations of all fingers of a user utilizing a 6DoF robotic arm. The system is developed using the Python programming language, leveraging the Mediapipe and OpenCV libraries. Mediapipe is employed to extract keypoints of the fingers in real-time, allowing for precise recognition of the joint positions of each finger. OpenCV processes the image data collected from the camera to analyze the finger positions, thereby enabling pose estimation. This approach is designed to maintain high accuracy despite varying lighting conditions and changes in hand position. The proposed system's performance has been validated through experiments, evaluating the accuracy of hand gesture recognition and the control capabilities of the robotic arm. The experimental results demonstrate that the system can estimate finger positions in real-time, facilitating precise movements of the 6DoF robotic arm. This research is expected to make significant contributions to the fields of robotic control and human-robot interaction, opening up various possibilities for future applications. The findings of this study will aid in advancing robotic technology and promoting natural interactions between humans and robots.