• Journal of Internet Computing and Services
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• v.23 no.1
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• pp.19-29
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• 2022

Natural user interface (NUI) is used for the natural motion interface without using a specific device or tool like a mouse, keyboards, and pens. Recently, as non-contact sensor-based interaction technologies for recognizing human motion, gestures, voice, and gaze have been actively studied, an environment has been prepared that can provide more diverse contents based on various interaction methods compared to existing methods. However, as the number of sensors device is rapidly increasing, the system using a lot of sensors can suffer from a lack of computational resources. To address this problem, we proposed a real-time multi-device control system for natural interactive platform. In the proposed system, we classified two types of devices as the HC devices such as high-end commercial sensor and the LC devices such astraditional monitoring sensor with low-cost. we adopt each device manager to control efficiently. we demonstrate a proposed system works properly with user behavior such as gestures, motions, gazes, and voices.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.501-507
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• 2012

Human body motion is a non-verbal part for interaction or movement that can be used to involves real world and virtual world. In this paper, we explain a study on natural user interface (NUI) in human hand motion recognition using RGB color information and depth information by Kinect camera from Microsoft Corporation. To achieve the goal, hand tracking and gesture recognition have no major dependencies of the work environment, lighting or users' skin color, libraries of particular use for natural interaction and Kinect device, which serves to provide RGB images of the environment and the depth map of the scene were used. An improved Camshift tracking algorithm is used to tracking hand motion, the experimental results show out it has better performance than Camshift algorithm, and it has higher stability and accuracy as well.

• Journal of the Ergonomics Society of Korea
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• v.31 no.4
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• pp.557-565
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• 2012

Objective: This paper focuses on the new trend of applying NUI(natural user interface) such as gesture interaction into television and investigates on the design improvement needed in application. The intention is to find better design direction of NUI on television context, which will contribute to making new features and behavioral changes occurring in next-generation television more practically usable and meaningful use experience elements. Background: Traditional television is rapidly evolving into next-generation television thanks to the influence of "smartness" from mobile domain. A number of new features and behavioral changes occurred from such evolution are on their way to be characterized as the new experience elements of next-generation television. Method: A series of expert review by television UX professionals based on AHP (Analytic Hierarchy Process) was conducted to check on the "relative appropriateness" of applying gesture interaction to a number of selected television user experience scenarios. Conclusion: It is critical not to indiscriminately apply new interaction techniques like gesture into television. It may be effective in demonstrating new technology but generally results in poor user experience. It is imperative to conduct consistent validation of its practical appropriateness in real context. Application: The research will be helpful in applying gesture interaction in next-generation television to bring optimal user experience in.

• Annual Conference of KIPS
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• 2016.10a
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• pp.382-385
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• 2016

본 논문은 현재 영역 별로 파편화된 여러 O2O(Online to Offline) 서비스들을 통합적으로 제공하기 위해 자연어를 통한 NUI(Natural User Interface)를 개발하여 사용자가 명시한 상품 정보의 항목을 자동으로 분류하고자 한다. 이를 위해 e-commerce 도메인 정보 학습에 적합한 나이브 베이즈 분류(Naive Bayes Classifier) 알고리즘을 사용한다. 학습에는 미국 e-commerce 사이트 Groupon의 상품 정보와 분류 체계를 사용하며, 학습 데이터의 특징을 분석하여 상품 정보에 특화된 학습 데이터 정제 및 TF-IDF(Term Frequency-Inverse Document Frequency)를 통한 단어 별 가중치를 적용하여 알고리즘의 정확도를 향상시킨다.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.473-480
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• 2014

As the use of computer has been popularized these days, an active research is in progress to make much more convenient and natural interface compared to the existing user interfaces such as keyboard or mouse. For this reason, there is an increasing interest toward Microsoft's motion sensing module called Kinect, which can perform hand motions and speech recognition system in order to realize communication between people. Kinect uses its built-in sensor to recognize the main joint movements and depth of the body. It can also provide a simple speech recognition through the built-in microphone. In this paper, the goal is to use Kinect's depth value data, skeleton tracking and labeling algorithm to recognize information about the extraction and movement of hand, and replace the role of existing peripherals using a virtual mouse, a virtual keyboard, and a speech recognition.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.5
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• pp.2363-2374
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• 2016

Communication occurs through verbal elements, which usually involve language, as well as non-verbal elements such as facial expressions, eye contact, and gestures. In particular, among these non-verbal elements, gestures are symbolic representations of physical, vocal, and emotional behaviors. This means that gestures can be signals toward a target or expressions of internal psychological processes, rather than simply movements of the body or hands. Moreover, gestures with such properties have been the focus of much research for a new interface in the NUI/NUX field. In this paper, we propose a method for recognizing the number of fingers and detecting the hand region based on the depth information and geometric features of the hand for application to an NUI/NUX. The hand region is detected by using depth information provided by the Kinect system, and the number of fingers is identified by comparing the distance between the contour and the center of the hand region. The contour is detected using the Suzuki85 algorithm, and the number of fingers is calculated by detecting the finger tips in a location at the maximum distance to compare the distances between three consecutive dots in the contour and the center point of the hand. The average recognition rate for the number of fingers is 98.6%, and the execution time is 0.065 ms for the algorithm used in the proposed method. Although this method is fast and its complexity is low, it shows a higher recognition rate and faster recognition speed than other methods. As an application example of the proposed method, this paper explains a Secret Door that recognizes a password by recognizing the number of fingers held up by a user.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.33-35
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• 2016

손 제스처는 스마트 글라스 등 웨어러블 기기의 NUI(Natural User Interface)를 구현하기 위한 수단으로 각광받고 있다. 최근 MPEG 에서는 IoT(Internet of Things) 및 웨어러블 환경에서의 미디어 소비를 지원하기 위한 IoMTW(Internet of Media-Things and Wearables) 표준화를 진행하고 있다. 본 논문에서는 손 제스처를 웨어러블 기기의 NUI 로 사용하여 웨어러블 기기 제어 및 미디어 소비를 제어하기 위한 손 제스처 검출과 인식 기법를 제시한다. 제시된 기법은 스테레오 영상으로부터 깊이 정보와 색 정보를 이용하여 손 윤곽선을 검출하여 이를 베지어(Bezier) 곡선으로 표현하고, 표현된 손 윤곽선으로부터 손가락 수 등의 특징을 바탕으로 제스처를 인식한다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2016.11a
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• pp.119-122
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• 2016

최근 IT기술 영역에서 미래기술로 촉망받는 증강현실(AR)과 가상현실(VR)환경을 구축함에 있어서, 마우스나 키보드 등의 별도 장치 없이 기기에 원하는 동작을 입력 하도록 하는 NUI(Natural User Interface)기술이 각광받고 있다. 또한 NUI를 구현하는데 중요한 기술 중 하나로 손동작 인식 기술, 얼굴 인식 기술 등이 대두되고 있다. 이에 본 논문은 적외선 센서의 일종인 Leapmotion 센서를 사용하여 손동작 인식을 구현하고자 하였다. 첫 번째로 우선 거리변환 행렬을 사용하여 손바닥의 중심을 찾았다. 이후 각각의 손가락을 convex hull 알고리즘을 사용하여 추출한다. 제안한 알고리즘에서는 손가락, 손바닥 부분의optical flow를 구한 후, 두 optical flow의 특성을 사용하여 손의 이동, 정지, 클릭 동작을 구분 할 수 있도록 하였다.

• Annual Conference of KIPS
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• 2014.11a
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• pp.1142-1144
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• 2014

본 논문에서는 뇌졸중, 치매 등 재활치료가 필요한 환자를 대상으로 하는 재활 프로그램을 Kinect와 Unity3D를 이용하여 구현하고, 이를 제어하기 위한 효과적인 제스처 기반 Natural User Interface를 적용하였다. 이는 동작 인식을 위해 Kinect 주변에 가까이 있기 어려운 프로그램 사용 환경을 원거리 조작이 가능케 하여 더욱 편하게 조작할 수 있게 하며, 직관적이고 단순한 제스처를 정의함으로써 가정에서도 손쉽게 사용할 수 있게 하였다.

• Annual Conference of KIPS
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• 2020.11a
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• pp.552-555
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• 2020

최근 코로나 관련 온라인 강의가 늘어남에 따라 적은 도구를 이용한 온라인과 오프라인 강의의 장점은 부각, 단점은 보완한 새로운 LMS가 필요함. 웹캠과 마이크를 이용하여 수강자의 수강태도를 파악 후, 수강자의 수업태도를 향상시키는 시스템임.