• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8563-8567
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• 2015

We propose a human-robot interaction(HRI) platform based on motion capture and mapping. Platform consists of capture, processing/mapping, and action parts. A motion capture sensor, computer, and avatar and/or physical robots are selected as capture, processing/mapping, and action part(s), respectively. Case studies-an interactive presentation and LEGO robot car are presented to show the design and implementation process of Kinect based HRI platform.

• Journal of Satellite, Information and Communications
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• v.9 no.1
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• pp.1-5
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• 2014

Recently, building is rapidly develop more intelligently because of the development of industries. And people seek such as comfort, efficiency, and convenience in office environment and the living environment. Also, people were able to use a variety of devices. Smart TV and smart phones were distributed widely so interaction between devices and human has been increase the interest. A various method study for interaction but there are some discomfort and limitations using controller for interaction. In this paper, a user could be easily interaction and control LED through using Kinect and gesture(hand gestures) without controller. we designed interface which is control LED using the joint information of gesture obtained from Kinect. A user could be individually controlled LED through gestures (hand movements) using the implementation of the interface. We expected developed interface would be useful in LED control and various fields.

• 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 Korean Institute of Industrial Engineers
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• v.40 no.1
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• pp.100-107
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• 2014

This paper presents a co-located and mobile interaction technique using smartphones in a global space. To effectively detect the locations and orientations of smartphones, the proposed approach utilizes Kinect that captures RGB image as well as 3D depth information. Based on the locations and orientations of smartphones, the proposed approach can support direct, collaborative and private interactions with the global space. Thus, it can provide more effective mobile interactions for local space exploration and collaboration.

• Journal of Computational Design and Engineering
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• v.2 no.2
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• pp.73-78
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• 2015

In this paper, we propose a new approach to providing interactive and collaborative lens among multi-users for supporting level-of-detailed views using smartphones in a public display. In order to provide smartphone-based lens capability, the locations of smartphones are effectively detected and tracked using Kinect, which provides RGB data and depth data (RGB-D). In particular, human skeleton information is extracted from the Kinect 3D depth data to calculate the smartphone location more efficiently and correctly with respect to the public display and to support head tracking for easy target selection and adaptive view generation. The suggested interactive and collaborative lens using smartphones not only can explore local spaces of the shared display but also can provide various kinds of activities such as LOD viewing and collaborative interaction. Implementation results are given to show the advantage and effectiveness of the proposed approach.

• Journal of Korea Multimedia Society
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• v.18 no.4
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• pp.557-564
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• 2015

There are many prior studies for more natural Human-Computer Interaction. Until now, the efforts is continued in order to recognize motions in various directions. In this paper, we suggest a user-specific recognition by hit detection method using Kinect camera and human proportion. This algorithm extracts the user-specific valid recognition rage after recognizing the user's body initially. And it corrects the difference in horizontal position between the user and Kinect, so that we can estimate a action of user by matching cursor to target using only one frame. Ensure that efficient hand recognition in the game to take advantage of this method of suggestion.

• Journal of The Korean Association of Information Education
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• v.23 no.4
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• pp.363-374
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• 2019

Recently, there is an increasing interest in game based learning as a teaching method for digital native learners. This study set kinect game contributes to engaged learning as the competition and cooperation play (achievement goals, interaction), the digital game play (multisensory stimulation, fantasy and curiosity, chance, accurate feedback, control), and the body movement play (embodied cognition, presence). After performing classes using the motion recognition game developed for the elementary school history class, this study conducted semi structured interviews based on engaged learning elements of kinect game based learning for students who were successfully participating in learning. In the result, each element appeared to a successful learner. Based on these results, this study hopes to assist researchers as a basic evidence to introduce kinect game-based learning for engaged learning.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.393-400
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• 2013

Hand shape recognition is a fundamental technique for implementing natural human-computer interaction. In this paper, we discuss a method for effectively detecting a hand region in Kinect-based hand shape recognition. Since Kinect is a camera that can capture color images and infrared images (or depth images) together, both images can be exploited for the process of detecting a hand region. That is, a hand region can be detected by finding pixels having skin colors or by finding pixels having a specific depth. Therefore, after analyzing the performance of each, we need a method of properly combining both to clearly extract the silhouette of hand region. This is because the hand shape recognition rate depends on the fineness of detected silhouette. Finally, through comparison of hand shape recognition rates resulted from different hand region detection methods in general environments, we propose a high-performance hand region detection method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.641-642
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• 2013

This research implemented Geostationary Ocean Color Imager (GOCI) observation satellite imagery visualization system on a large high-resolution tiled display. This system is designed to help users observe or analyze satellite imagery more effectively on the tiled display using multi-touch and Kinect motion gesture recognition interaction. We developed the multi-scale image loading and rendering technique for the massive amount of memory management and smooth rendering for GOCI satellite imagery on the tiled display. In this system, the unit of time corresponding to the selected date of the satellite images are sequentially displayed on the screen. Users can zoom-in, zoom-out, move the imagery and select some buttons to trigger functions using both multi-touch or Kinect gesture interaction.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.11
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• pp.2727-2732
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• 2014

Recently, the researches of object tracking and recognition using Microsoft's Kinect are being actively studied. In this environment human hand detection and tracking is the most basic technique for human computer interaction. This paper proposes a method of improving the accuracy of the detected hand region's boundary in the cluttered background. To do this, we combine the hand detection results using the skin color with the extracted depth image from Kinect. From the experimental results, we show that the proposed method increase the accuracy of the hand region detection than the method of detecting a hand region with a depth image only. If the proposed method is applied to the sign language or gesture recognition system it is expected to contribute much to accuracy improvement.