• Journal of Advanced Navigation Technology
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• v.18 no.6
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• pp.619-624
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• 2014

Nowadays there are various smart devices and development with the development of smart phones and that can be attached to the human body wearable computing device has been in the spotlight. In this paper, we proceeded developing wearable devices in watch type which can detect user's movement and developing a system which connects the wearable devices to smart TVs, or smart phones so that users can save and manage their physical information in those devices. Health care wearable devices already existing save information by connecting their systems to smart phones. And, smart TV health applications usually include motion detecting systems using cameras. However, there is a limit when connecting smart phone systems to different devices from various companies. Also, in case of smart TV, because some devices may not have cameras, there can be a limit for users who wants to connect their devices to smart TVs. Wearable device and user information collected by using the smart phone and when it is possible to exercise and manage anywhere. This information can also be confirmed by the smart TV applications. By using this system will be able to take advantage of the study of the behavior of the future work of the user more accurately be measured in recognition technology and other devices.

• Proceedings of the Korean Society of Computer Information Conference
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• 2016.01a
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• pp.133-136
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• 2016

NUI는 마우스, 키보드 등의 HID장치를 사용하지 않고 사용자의 신체를 사용하여 장치를 제어하는 모션 인터페이스이다. 본 논문에서는 소형 임베디드보드 라즈베리파이와 라즈베리파이에 연결된 파이카메라를 통해 영상인식과 컴퓨터 비전을 위하여 최적화된 알고리즘을 제공하는 OpenCV를 이용하여 손의 제스처를 인식하여 기존 HID장비와 비교하여 더욱 인간 친화적이며 직관적인 NUI장치 인터페이스를 구현하고자 한다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.6
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• pp.209-214
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• 2010

In this paper, We analyzes the image along the platform (Open Eye), through prevention of dementia or stroke patients and cognitive rehabilitation for the proposed system. This way through the camera image according to user's movement gained OpenCV image processing library, which is based on motion analysis, a part of this rehabilitation is to apply to cognitive rehabilitation. Therefore, this paper proposes a new image analysis system has been exposed to the elderly or stroke patients with dementia, their hand gestures through which patients can detect the image of the cognitive rehabilitation to help them in the analysis of the image analysis system is proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.396-399
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• 2018

In this paper, we propose a motion recognition system for identification and interaction with simulator used in the realistic biathlon simulator. The proposed system tried to improve the motions data which is obstructed by the obstacles or overlapping joints and the motion due to the fast motion in the process of recognizing the various motion patterns in the biathlon. In this paper, we constructed a multi-camera motion recognition system based on IoT devices, and then we applied a skeletal area interpolation method for normal motion identification. We designed a system that can increase the recognition rate of motion from the biathlon. The proposed system can be applied to the analysis of snow sports motion and it will be used to develop realistic biathlon simulator system.

• KIISE Transactions on Computing Practices
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• v.23 no.3
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• pp.148-155
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• 2017

In this paper, we develop a new system to estimate the step count for a smartphone user. The system analyzes data obtained from the accelerometer, magnetic sensor, and gyroscope of an android smartphone to extract pattern information of human steps. We conduct an experiment and evaluation to confirm that the proposed system successfully estimates the number of steps with 96% accuracy when hand-held and 95.5% accuracy when in-pocket. In addition, we found that detection errors were caused by human motions such as touching the screen, shaking the device up and down, sitting up and sitting down, and waving the phone around.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.800-801
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• 2017

Location-based services (LBS) are used in various applications such as emergency support, navigation, location, traffic routes, information gathering, and entertainment due to the rapid growth of information communication technologies and mobile phones. In general, locations are represented by coordinates and are related to terrain. These are of great interest in mobile-based data transmission. This paper proposes a method to exchange the contact of the other party by detecting the movement of the mobile phone of the individual user based on the location-based service. The proposed method extracts motion using the acceleration sensor of the mobile phone and transmits the location and time information to the server when the motion continues for a predetermined time. Attempts to establish a connection between users who are experiencing motion in mobile phones in the short distance have been made from the server. Once the connection between the users is made, the encrypted contact is received from the server. Experimental results show that the proposed method can exchange data by minimizing the processing in the handset compared with the existing method.

• Journal of Broadcast Engineering
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• v.25 no.4
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• pp.545-559
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• 2020

In this paper, we propose a content creation framework that enables users without programming experience to easily create interactive media content that responds to user gestures. In the proposed framework, users define the gestures they use and the media effects that respond to them by numbers, and link them in a text-based configuration file. In the proposed framework, the interactive media content that responds to the user's gesture is linked with the dynamic projection mapping module to track the user's location and project the media effects onto the user. To reduce the processing speed and memory burden of the gesture recognition, the user's movement is expressed as a gray scale motion history image. We designed a convolutional neural network model for gesture recognition using motion history images as input data. The number of network layers and hyperparameters of the convolutional neural network model were determined through experiments that recognize five gestures, and applied to the proposed framework. In the gesture recognition experiment, we obtained a recognition accuracy of 97.96% and a processing speed of 12.04 FPS. In the experiment connected with the three media effects, we confirmed that the intended media effect was appropriately displayed in real-time according to the user's gesture.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.01a
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• pp.55-56
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• 2020

본 논문에서는 키넥트 센서 기반의 노인 건강 관리 애플리케이션을 설계하고 구현한다. 이 애플리케이션은 체조하기 모드와 두뇌 게임 모드로 구성한다. 체조하기 모드는 모션 인식 기능을 활용하여 스트레칭을 비롯한 다양한 체조 동작을 반복적으로 따라 함으로써 사용자의 건강을 관리할 수 있는 기능을 제공한다. 두뇌게임 모드는 사용자의 기억력을 증진함으로써 치매를 예방할 수 있는 기능을 제공한다. 또한, Unity의 핸드트래킹 기술을 이용하여 두뇌 게임을 하는 동시에 자연스레 팔과 어깨의 운동을 할 수 있도록 게임 화면을 구성한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2022.11a
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• pp.773-775
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• 2022

영상처리 기술의 발달로 영상처리 기술을 이용한 다양한 어플리케이션이 출시되고 있다. 영상처리 기술로 영상의 정보를 디지털화 할 수 있는 점에 착안해 춤 실력을 평가하는 시스템을 고안했다. 본 작품에서는 Human Pose Estimation 기술로 사람의 관절 위치 정보를 파악하고, 춤 전문가의 관절 위치와 사용자의 관절 위치를 동작 비교 알고리즘을 통해 비교해 사용자가 춤을 얼마나 정확하게 추는지 수치적으로 점수화해 제공한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.1088-1091
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• 2017

최근 그래픽스 기반의 가상현실 기술의 발전과 관심이 증가하면서 3D 객체와의 자연스러운 상호작용을 위한 방법들 중 손 제스처 인식에 대한 연구가 활발히 진행되고 있다. 본 논문은 가상현실 3D 오브젝트와의 상호작용을 위한 MCSVM 기반의 손 제스처 인식을 제안한다. 먼저 다양한 손 제스처들을 립모션을 통해 입력 받아 전처리를 수행한 손 데이터를 전달한다. 그 후 이진 결정 트리로 1차 분류를 한 손 데이터를 리샘플링 한 뒤 체인코드를 생성하고 이에 대한 히스토그램으로 특징 데이터를 구성한다. 이를 기반으로 MCSVM 학습을 통해 2차 분류를 수행하여 제스처를 인식한다. 실험 결과 3D 오브젝트와 상호작용을 위한 16개의 명령 제스처에 대해 평균 99.2%의 인식률을 보였고 마우스 인터페이스와 비교한 정서적 평가 결과에서는 마우스 입력에 비하여 직관적이고 사용자 친화적인 상호작용이 가능하다는 점에서 게임, 학습 시뮬레이션, 설계, 의료분야 등 많은 가상현실 응용 분야에서의 입력 인터페이스로 활용 될 수 있고 가상현실에서 몰입도를 높이는데 도움이 됨을 알 수 있었다.