• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.231-232
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• 2014

We develop a remote control system of a walking robot using a Leap motion sensor. Hand gestures and the position of fingers are provided from the Leap motion sensor. We use Processing and the LeapMotionP5 library for the development software.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.3
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• pp.463-470
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• 2023

In this study, an electronic parts assembly training system using Leap Motion was developed in consideration of the processes actually operated in the assembly process of electronic products. Based on Leap Motion and Oculus VR equipment, the system was developed to transfer user's hand movement data in real time and convert it into hand movement in virtual space so that electronic parts assembly simulation can be performed step by step. Through this, it was confirmed that the user can obtain an experience similar to the actual electronic parts assembly work, prevent errors that may occur during the assembly process, and improve proficiency. It is expected that this thesis will provide directions for the quality improvement and development of various education and training programs for virtual reality-based manufacturing processes.

• Korean Journal of Computational Design and Engineering
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• v.21 no.2
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• pp.159-169
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• 2016

In order to realize the virtual prototyping (VP) of digital products, it is important to provide the people involved in product development with the appropriate visualization and interaction of the products, and the vivid simulation of user interface (UI) behaviors in an interactive 3D virtual environment. In this paper, we propose an approach to web-based 3D virtual experience using Unity and Leap Motion. We adopt Unity as an implementation platform which easily and rapidly implements the visualization of the products and the design and simulation of their UI behaviors, and allows remote users to get an easy access to the virtual environment. Additionally, we combine Leap Motion with Unity to embody natural and immersive interaction using the user's hand gesture. Based on the proposed approach, we have developed a testbed system for web-based 3D virtual experience and applied it for the design evaluation of various digital products. Button selection test was done to investigate the quality of the interaction using Leap Motion, and a preliminary user study was also performed to show the usefulness of the proposed approach.

• 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.

• Journal of Biomedical Engineering Research
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• v.42 no.4
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• pp.186-192
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• 2021

In this paper, we evaluated prediction accuracy of Euler angle spectrograph classification method using a convolutional neural networks (CNN) for hand gesture recognition in augmented reality (AR) cognitive rehabilitation system based on Leap Motion Controller (LMC). Hand gesture recognition methods using a conventional support vector machine (SVM) show 91.3% accuracy in multiple motions. In this paper, five hand gestures ("Promise", "Bunny", "Close", "Victory", and "Thumb") are selected and measured 100 times for testing the utility of spectral classification techniques. Validation results for the five hand gestures were able to be correctly predicted 100% of the time, indicating superior recognition accuracy than those of conventional SVM methods. The hand motion recognition using CNN meant to be applied more useful to AR cognitive rehabilitation training systems based on LMC than sign language recognition using SVM.

• Journal of Digital Contents Society
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• v.19 no.2
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• pp.319-325
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• 2018

The general public's interest in dementia has increased recently as dementia has become a social issue due to its rapid aging. Several dementia prevention and rehabilitation programs are being carried out at the dementia rehabilitation center and at the old welfare center depending on the number of dementia patients. In this paper, a 3 dimensional finger and motion search of the leap motion is utilized and combined with dementia preventive and cognitive rehabilitation programs at various facilities. We suggest technologies that can provide both fun and effective treatment and rehabilitation content for rehabilitation therapists. A variety of cognitive enhancement content is designed using finger tracking and configured to be recorded in the database for rehabilitation programmes to increase the effectiveness of management.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1041-1044
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• 2017

말하기와 듣기가 불가능한 언어장애인들은 수화를 통하여 그들끼리 혹은 일반인과 의사소통을 해야 한다. 수화 또한 공용어이기에 전문통역사 없이도 서로간의 의사소통이 원활해야 하지만, 현실은 그렇지 않다. 이 시스템은 LeapMotion장비를 연결 및 각종 손동작을 인식 받아 데이터 세트 내에서 처리하여 이를 자연어로 변환함으로써 의사소통의 불편함을 해소할 수 있다. 또한 머신러닝을 이용하여 반복 학습할 수 있게 설계함으로써 처리율 향상을 기대할 수 있다.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.6
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• pp.1127-1134
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• 2017

In this study, the robot arm control system was implemented that is operated by human hands, which can be used in environments that are inaccessible to humans. This function has to be sent to the robot's arms after extracting coordinates of human hands. Through mapping and bluetooth communication we use a leap motion sensor with infrared light and Image recognition sensor.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.333-334
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• 2018

This is a study on controlling a drone (DJI Mavic Air) with simple hand gesture using Leap Motion controller. Four component involve are MacBook, Leap Motion controller, Android device, and DJI Mavic Air. All of this component are connected through USB, Bluetooth, and Wi-Fi technology. The studies main purpose are to show that by controlling a drone through Leap Motion, drone amateur user can easily learn how to control a drone, and because of longer drone control range can be archived things such as search and rescue mission will be possible.

• Journal of Digital Contents Society
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• v.17 no.4
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• pp.287-293
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• 2016

Some studies require sufficient amount of time, spaces, and financial condition for practical exercises and training. In particular for the Medical education, time and space limitation is very high and difficulties occurs, since the practices are done with cadavers (deceased human body). Many alternate 3D Virtual surgery training system exist currently, however the burdensome of obtaining those costly equipments is problematic. Providing the surgical environment as similar to real as possible using 3D Virtual Reality can be a solution to current problems. The effectiveness of training could be maximized with minimized costs without the general interfaces such as keyboard and mouse, but with Oculus Rift and Leap Motion. This paper will develop and practice the 3D Virtual Operation System with two devices to investigate the possibility and expand to other Simulation fields.