• Journal of the Ergonomics Society of Korea
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• v.35 no.6
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• pp.519-533
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• 2016

Objective: This study lays its aims at the definition of relevant operation method and function by researching on the value to be brought when applying smart device that can hand carry soft and flexible materials like jelly. Background: New technology and material play a role in bringing type transformation of interface and change of operation system. Recently, importance has been increased on the study of Organic User Interface (OUI) that conducts research on the value of new method of input and output adopting soft and flexible materials for various instruments. Method: For fulfillment of the study, 27 kinds of gestures have been defined that are usable in handheld device based on existing studies. Quantitative research of survey was conducted of adult male and female of 20s through 30s and an analysis was done on the function that can be linked to gestures with highest level of satisfaction. In order to analyze needs and hurdles of users for the defined gesture, a focus group interview was conducted aiming at the groups of early adopters and ordinary users. Results: As a result, it was found that users have much value regarding usability and fun for elastic device and analysis could be conducted on preferred gesture and its linkable functions. Conclusion: What is most significant with this study is that it sheds new light on the values of a device made of elastic material. Beyond finding and defining the gestures and functions that can be applied to a handheld elastic device, the present study identified the value elements of an elastic device - 'usability and 'fun' -, which users can basically desire from using it. Application: The data that this study brought forth through preference and satisfaction test with the gestures and associated functions will help commercialize an elastic device in future.

• Journal of Broadcast Engineering
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• v.16 no.6
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• pp.941-950
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• 2011

With the recent advance in the performance of mobile phones, many effective interfaces for them have been proposed. This paper implements a hand-gesture-and-vision-based interface on a mobile phone. This paper assumes natural interaction scenario when user holds a mobile phone in a hand and sees the other hand's palm through mobile phone's camera. Then, a virtual object is rendered on his/her palm and reacts to hand and finger movements. Since the implemented interface is based on hand familiar to humans and does not require any additional sensors or markers, user freely interacts with the virtual object anytime and anywhere without any training. The implemented interface worked at 5 fps on mobile phone (Galaxy S2 having a dual-core processor).

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.664-667
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• 2009

There is strong demand to create wearable PC systems that can support the user outdoors. When we are outdoors, our movement makes it impossible to use traditional input devices such as keyboards and mice. We propose a hand gesture interface based on image processing to operate wearable PCs. The semi-transparent PC screen is displayed on the head mount display (HMD), and the user makes hand gestures to select icons on the screen. The user's hand is extracted from the images captured by a color camera mounted above the HMD. Since skin color can vary widely due to outdoor lighting effects, a key problem is accurately discrimination the hand from the background. The proposed method does not assume any fixed skin color space. First, the image is divided into blocks and blocks with similar average color are linked. Contiguous regions are then subjected to hand recognition. Blocks on the edges of the hand region are subdivided for more accurate finger discrimination. A change in hand shape is recognized as hand movement. Our current input interface associates a hand grasp with a mouse click. Tests on a prototype system confirm that the proposed method recognizes hand gestures accurately at high speed. We intend to develop a wider range of recognizable gestures.

• Journal of the Korea Computer Graphics Society
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• v.24 no.5
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• pp.41-48
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• 2018

The most natural way to increase immersion and provide free interaction in a virtual environment is to provide a gesture interface using the user's hand. However, most studies about hand gesture recognition require specialized sensors or equipment, or show low recognition rates. This paper proposes a three-dimensional DenseNet Convolutional Neural Network that enables recognition of hand gestures with no sensors or equipment other than an RGB camera for hand gesture input and introduces a virtual reality game based on it. Experimental results on 4 static hand gestures and 6 dynamic hand gestures showed that they could be used as real-time user interfaces for virtual reality games with an average recognition rate of 94.2% at 50ms. Results of this research can be used as a hand gesture interface not only for games but also for education, medicine, and shopping.

• Journal of the Korea Society of Computer and Information
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• v.17 no.10
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• pp.43-53
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• 2012

In the this paper, a gesture-based user interface based on object detection using predefined gesture and the tracking of the detected object is proposed. For object detection, moving objects in a frame are computed by comparing multiple previous frames and predefined gesture is used to detect the target object among those moving objects. Any object with the predefined gesture can be used to control. We also propose an object tracking algorithm, namely density based meanshift algorithm, that uses color distribution of the target objects. The proposed object tracking algorithm tracks a target object crossing the background with a similar color more accurately than existing techniques. Experimental results show that the proposed object detection and tracking algorithms achieve higher detection capability with less computational complexity.

• Korean Journal of Computational Design and Engineering
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• v.21 no.1
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• pp.20-30
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• 2016

Recently immersive virtual reality (VR) becomes popular due to the advanced development of I/O interfaces and related SWs for effectively constructing VR environments. In particular, natural and intuitive manipulation of 3D virtual objects is still considered as one of the most important user interaction issues. This paper presents a comparative study on the manipulation and interaction of 3D virtual objects using different interfaces and interactions in three VR environments. The comparative study includes both quantitative and qualitative aspects. Three different experimental setups are 1) typical desktop-based VR using mouse and keyboard, 2) hand gesture-supported desktop VR using a Leap Motion sensor, and 3) immersive VR by wearing an HMD with hand gesture interaction using a Leap Motion sensor. In the desktop VR with hand gestures, the Leap Motion sensor is put on the desk. On the other hand, in the immersive VR, the sensor is mounted on the HMD so that the user can manipulate virtual objects in the front of the HMD. For the quantitative analysis, a task completion time and success rate were measured. Experimental tasks require complex 3D transformation such as simultaneous 3D translation and 3D rotation. For the qualitative analysis, various factors relating to user experience such as ease of use, natural interaction, and stressfulness were evaluated. The qualitative and quantitative analyses show that the immersive VR with the natural hand gesture provides more intuitive and natural interactions, supports fast and effective performance on task completion, but causes stressful condition.

• Journal of Korea Game Society
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• v.15 no.1
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• pp.27-34
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• 2015

This paper proposes a user interface for enhancing immersiveness and usability by combining hologram and haptic device with common Leap Motion. While Leap Motion delivers physical motion of user hand to control virtual environment, it is limited to handle virtual hands on screen and interact with virtual environment in one way. In our system, hologram is coupled with Leap Motion to improve user immersiveness by arranging real and virtual hands in the same place. Moreover, we provide a interaction prototype of sense by designing a haptic device to convey touch sense in virtual environment to user's hand.

• International Journal of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.71-76
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• 2018

The technology convergence of television, communication, and computing devices enables the rich social and entertaining experience through Smart TV in personal living space. The powerful smart TV computing platform allows to provide various user interaction interfaces like IR remote control, web based control, body gesture based control, etc. The presently used smart TV interaction user control methods are not efficient and user-friendly to access different type of media content and services and strongly required advanced way to control and access to the smart TV with easy user interface. This paper propose the optical wireless communication (OWC) based remote controller design for Smart TV using smart device Flashlights. In this approach, the user smart device act as a remote controller with touch based interactive smart device application and transfer the user control interface data to smart TV trough Flashlight using visible light communication method. The smart TV built-in camera follows the optical camera communication (OCC) principle to decode data and control smart TV user access functions according. This proposed method is not harmful as radio frequency (RF) radiation does it on human health and very simple to use as well user does need to any gesture moves to control the smart TV.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.621-625
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• 2010

This paper presents a hand motion tracking method for hand gesture interface using a camera in mobile devices such as a smart phone and PDA. When a camera moves according to the hand gesture of the user, global optical flows are generated. Therefore, robust hand movement estimation is possible by considering dominant optical flow based on histogram analysis of the motion direction. A continuous hand gesture is segmented into unit gestures by motion state estimation using motion phase, which is determined by velocity and acceleration of the estimated hand motion. Feature vectors are extracted during movement states and hand gestures are recognized at the end state of each gesture. Support vector machine (SVM), k-nearest neighborhood classifier, and normal Bayes classifier are used for classification. SVM shows 82% recognition rate for 14 hand gestures.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.246-252
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• 2018

Hand gestures are attracting attention as a NUI (Natural User Interface) of wearable devices such as smart glasses. Recently, to support efficient media consumption in IoT (Internet of Things) and wearable environments, the standardization of IoMT (Internet of Media Things) is in the progress in MPEG. In IoMT, it is assumed that hand gesture detection and recognition are performed on a separate device, and thus provides an interoperable interface between these modules. Meanwhile, deep learning based hand gesture recognition techniques have been recently actively studied to improve the recognition performance. In this paper, we propose a method of hand gesture recognition based on CNN (Convolutional Neural Network) for various applications such as media consumption in wearable devices which is one of the use cases of IoMT. The proposed method detects hand contour from stereo images acquisitioned by smart glasses using depth information and color information, constructs data sets to learn CNN, and then recognizes gestures from input hand contour images. Experimental results show that the proposed method achieves the average 95% hand gesture recognition rate.