• Journal of the Korea Society of Computer and Information
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• v.24 no.4
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• pp.57-63
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• 2019

In this paper, we propose a new framework to control VR(Virtual reality) contents in real time using user's mouth-wind and acceleration sensor of mobile device. In VR, user interaction technology is important, but various user interface methods is still lacking. Most of the interaction technologies are hand touch screen touch or motion recognition. We propose a new interface technology that can interact with VR contents in real time using user's mouth-wind method with acceleration sensor. The direction of the mouth-wind is determined using the angle and position between the user and the mobile device, and the control position is adjusted using the acceleration sensor of the mobile device. Noise included in the size of the mouth wind is refined using a simple average filter. In order to demonstrate the superiority of the proposed technology, we show the result of interacting with contents in game and simulation in real time by applying control position and mouth-wind external force to the game.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.4
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• pp.180-185
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• 2018

We have developed an interactive signage system based on floating hologram by combining hologram technology and ICT technology, which can be competitive to small businesses that have excellent products and services. The developed interactive signage system can be used for publicity and marketing of small business owners at low cost, introducing menus with 3D hologram images, and providing various contents responding to user's hand movements. The developed system is able to detect 10 finger movements at a rate of 290 frames per second in a range of 60cm and a range of 150 degrees. We also confirmed that the virtual touch function operates normally by dividing the user's motion recognition into the hover zone and the touch zone by the physical motion experiment of the leap motion object.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.1 s.307
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• pp.17-26
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• 2006

This paper proposes a novel hidden Markov model (HMM)-based gesture recognition method and applies it to an HCI to control a computer game. The novelty of the proposed method is two-fold: 1) the proposed method uses a continuous streaming of human motion as the input to the HMM instead of isolated data sequences or pre-segmented sequences of data and 2) the gesture segmentation and recognition are performed simultaneously. The proposed method consists of a single HMM composed of thirteen gesture-specific HMMs that independently recognize certain gestures. It takes a continuous stream of pose symbols as an input, where a pose is composed of coordinates that indicate the face, left hand, and right hand. Whenever a new input Pose arrives, the HMM continuously updates its state probabilities, then recognizes a gesture if the probability of a distinctive state exceeds a predefined threshold. To assess the validity of the proposed method, it was applied to a real game, Quake II, and the results demonstrated that the proposed HMM could provide very useful information to enhance the discrimination between different classes and reduce the computational cost.

• IEMEK Journal of Embedded Systems and Applications
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• v.15 no.1
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• pp.35-42
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• 2020

In this paper, we propose a method to keep the robot at a distance of 30 to 45cm from the user in consideration of each individual's minimum area and inconvenience by using a 2D LiDAR sensor LDS-01 as the secondary sensor along with a QR code. First, the robot determines the brightness of the video and the presence of a QR code. If the light is bright and there is a QR code due to human's presence, the range of the 2D LiDAR sensor is set based on the position of the QR code in the captured image to find and follow the correct target. On the other hand, when the robot does not recognize the QR code due to the low light, the target is followed using a database that stores obstacles and human actions made before the experiment using only the 2D LiDAR sensor. As a result, our robot can follow the target person in four situations based on nine locations with seven types of motion.

• The Academic Congress of Korean Shoulder and Elbow Society
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• 2008.03a
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• pp.165-165
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• 2008

A 27-year-old, right-hand-dominant woman with a posttraumatic anterior shoulder dislocation 3 months earlier after traYc accident presented because of pain and limited range of motion in the right shoulder. On physical examination, the patient had negative instability tests and a sulcus sign. On arthroscopic examination, a bifurcate long biceps tendon with two limbs was observed about 1 cm distal to the origin in the supraglenoid tubercle. We found no evidence of a tear in the long biceps tendon on probing, and the margin of each limb was smooth and round. Although this anatomic variant may be benign, its presence might be associated with other shoulder pathology. It is interesting to speculate whether the aberrant biceps anatomy in our patient contributed to transfer of injury at dislocation to the rotator cuff rather than to the classic anterior-inferior capsulolabral complex. In addition, recognition of the described anatomic variant on arthroscopy can aid the shoulder surgeon in focusing treatment on the actual pathology.

• Journal of Korea Multimedia Society
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• v.19 no.1
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• pp.60-67
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• 2016

PC users have long been controlling their computers using input devices such as mouse and keyboard. To improve inconveniences of these devices, the method of screen-touching has widely been used these days, and devices recognizing human gestures are being developed one after another. Fox example, Kinect, developed and distributed by Microsoft, is a non-contact input device that recognizes human gestures through motion-recognizing sensors, thus replacing the mouse as an input device. However, when controlling the mouse on a large screen, it suffers from the problem of requiring large motions in order to move the mouse pointer to the edges of the screen. In this paper, we propose a joystick-driven mouse-controlling method which enables the user to move the mouse pointer to the corners of the screen with small motions. The experimental results show that movements of the user's palm within the range of 30 cm ensure movements of the mouse pointer to the edges of the screen.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.811-814
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• 2009

The cost competitive products buyers through the e-commerce are growing steadily every year due to the development of the Internet. Furniture and home appliances buyers through the e-commerce, on the other hand, aren't growing cause it's impossible to check the size and harmony with interior. Therefore, in this paper, we introduce arrangement system for furniture and home appliances based on augmented reality and motion recognition to provide service which checks the size and harmony with interior by arranging them virtually before purchasing.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.77-82
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• 2022

GUI(Graphical User Interface)를 대신하는 차세대 인터페이스로서 NUI(Natural User Interace)에 기대가 모이는 것은 자연스러운 흐름이다. 본 연구는 NUI의 손가락 관절을 포함한 손동작 전체를 인식시키기 위해 웹캠과 카메라를 활용하여 다양한 배경과 각도의 손동작 데이터를 수집한다. 수집된 데이터는 전처리를 거쳐 데이터셋을 구축하며, ResNet50 모델을 활용하여 전이학습한 합성곱 신경망(Convolutional Neural Network) 알고리즘 분류기를 설계한다. 구축한 데이터셋을 입력시켜 분류학습 및 예측을 진행하며, 실시간 영상에서 인식되는 손동작을 설계한 모델에 입력시켜 나온 결과를 통해 가위바위보 게임을 구현한다.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.380-392
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• 2013

A method to classify a golf swing motion into 7 sections using a Kinect sensor and a fuzzy system is proposed. The inputs to the fuzzy logic are the positions of golf club and its head, which are extracted from the information of golfer's joint position and color information obtained by a Kinect sensor. The proposed method consists of three modules: one for extracting the joint's information, another for detecting and tracking of a golf club, and the other for classifying golf swing motions. The first module extracts the hand's position among the joint information provided by a Kinect sensor. The second module detects the golf club as well as its head with the Hough line transform based on the hand's coordinate. Using a fuzzy logic as a classification engine reduces recognition errors and, consequently, improves the performance of robust classification. From the experiments of real-time video clips, the proposed method shows the reliability of classification by 85.2%.

• The Transactions of the Korea Information Processing Society
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• v.4 no.12
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• pp.3033-3044
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• 1997

This paper presents a system which recognizes dynamic hand gesture for virtual reality (VR). A dynamic hand gesture is a method of communication for human and computer who uses gestures, especially both hands and fingers. Since the human hands and fingers are not the same in physical dimension, the produced by two persons with their hands may not have the same numerical values where obtained through electronic sensors. To recognize meaningful gesture from continuous gestures which have no token of beginning and end, this system segments current motion states using the state automata. In this paper, we apply a fuzzy min-max neural network and feature analysis method using fuzzy logic for on-line pattern recognition.