• Journal of the Ergonomics Society of Korea
• /
• v.31 no.4
• /
• pp.567-575
• /
• 2012

Objective: The aim of this study is to get an optimal mental model by investigating user's natural behavior for controlling smart TV by mid-air gestures and to identify which factor is most important for controlling behavior. Background: A lot of TV companies are trying to find simple controlling method for complex smart TV. Although plenty of gesture studies proposing they could get possible alternatives to resolve this pain-point, however, there is no fitted gesture work for smart TV market. So it is needed to find optimal gestures for it. Method: (1) Eliciting core control scene by in-house study. (2) Observe and analyse 20 users' natural behavior as types of hand-held devices and control scene. We also made taxonomies for gestures. Results: Users' are trying to do more manipulative gestures than symbolic gestures when they try to continuous control. Conclusion: The most natural way to control smart TV on the remote with gestures is give user a mental model grabbing and manipulating virtual objects in the mid-air. Application: The results of this work might help to make gesture interaction guidelines for smart TV.

• Journal of Korea Society of Industrial Information Systems
• /
• v.13 no.4
• /
• pp.145-154
• /
• 2008

In this paper, we propose the pet robot control system using hand gesture recognition in image sequences acquired from a camera affixed to the pet robot. The proposed system consists of 4 steps; hand detection, feature extraction, gesture recognition and robot control. The hand region is first detected from the input images using the skin color model in HSI color space and connected component analysis. Next, the hand shape and motion features from the image sequences are extracted. Then we consider the hand shape for classification of meaning gestures. Thereafter the hand gesture is recognized by using HMMs (hidden markov models) which have the input as the quantized symbol sequence by the hand motion. Finally the pet robot is controlled by a order corresponding to the recognized hand gesture. We defined four commands of sit down, stand up, lie flat and shake hands for control of pet robot. And we show that user is able to control of pet robot through proposed system in the experiment.

• Journal of Institute of Control, Robotics and Systems
• /
• v.10 no.9
• /
• pp.771-778
• /
• 2004

Recently, various applications of robot system become more popular in accordance with rapid development of computer hardware/software, artificial intelligence, and automatic control technology. Formerly robots mainly have been used in industrial field, however, nowadays it is said that the robot will do an important role in the home service application. To make the robot more useful, we require further researches on implementation of natural communication method between the human and the robot system, and autonomous behavior generation. The gesture recognition technique is one of the most convenient methods for natural human-robot interaction, so it is to be solved for implementation of intelligent robot system. In this paper, we describe the state-of-the-art of advanced gesture recognition technologies for intelligent robots according to three methods; sensor based method, feature based method, appearance based method, and 3D model based method. And we also discuss some problems and real applications in the research field.

• Journal of Korea Multimedia Society
• /
• v.17 no.11
• /
• pp.1263-1269
• /
• 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.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2012.04a
• /
• pp.436-439
• /
• 2012

The work is to the control the desktop Computers based on hand gesture recognition. This paper is worked en real time tracking and recognizes the hand gesture for controlling the slides based on hand direction such as right and left using a real time camera.

• Educational Technology International
• /
• v.16 no.2
• /
• pp.141-166
• /
• 2015

The purpose of this study was to examine the effects of using visual stimulation and gesture, namely embodied language learning, on learning achievement and learner's course interest in the EFL classroom. To investigate the effectiveness of the proposed purpose, thirty two third-grade elementary school students participated and were assigned into four English learning class conditions (i.e., using animated graphic and gestures condition, using only animated graphic condition, using still pictures and gesture condition, and control condition). The research questions for this study are addressed below: (1) What differences are there in post and delayed learning achievement between imitating gesture group and non-imitating one and between animated graphic group and still picture one? (2) What differences are there in course interest between imitating gesture group and non-imitating one and between animated graphic group and still picture one? The Embodiment-based English learning system for this study was designed by using Microsoft's Kinect sensing devices. The results of this study revealed that students of imitating gesture group memorized and retained better words and sentence structure than those of the other groups. As for learner's course interest measurement, imitating gesture group showed a highly positive response to attention, relevance, and satisfaction for curriculum and using animated graphic influenced satisfaction as well. This finding can be attributed to the embodied cognition, which proposes that the body and the mind are inseparable in the constitution of cognition and thus students using visual simulation and imitating related gesture regard the embodied language learning approach more satisfactory and acceptable than the conventional ones.

• Journal of the Ergonomics Society of Korea
• /
• v.31 no.4
• /
• pp.593-599
• /
• 2012

Objective: This study aims to implement a non-contact gesture-based interface for presentation purposes and to analyze the effect of the proposed interface as information transfer assisted device. Background: Recently, research on control device using gesture recognition or speech recognition is being conducted with rapid technological growth in UI/UX area and appearance of smart service products which requires a new human-machine interface. However, few quantitative researches on practical effects of the new interface type have been done relatively, while activities on system implementation are very popular. Method: The system presented in this study is implemented with KINECT$^{(R)}$ sensor offered by Microsoft Corporation. To investigate whether the proposed system is effective as a presentation support tool or not, we conduct experiments by giving several lectures to 40 participants in both a traditional lecture room(keyboard-based presentation control) and a non-contact gesture-based lecture room(KINECT-based presentation control), evaluating their interests and immersion based on contents of the lecture and lecturing methods, and analyzing their understanding about contents of the lecture. Result: We check that whether the gesture-based presentation system can play effective role as presentation supporting tools or not depending on the level of difficulty of contents using ANOVA. Conclusion: We check that a non-contact gesture-based interface is a meaningful tool as a sportive device when delivering easy and simple information. However, the effect can vary with the contents and the level of difficulty of information provided. Application: The results presented in this paper might help to design a new human-machine(computer) interface for communication support tools.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.2
• /
• pp.787-806
• /
• 2016

Traditional radio-based gesture recognition approaches usually require the target to carry a device (e.g., an EMG sensor or an accelerometer sensor). However, such requirement cannot be satisfied in many applications. For example, in smart home, users want to control the light on/off by some specific hand gesture, without finding and pressing the button especially in dark area. They will not carry any device in this scenario. To overcome this drawback, in this paper, we propose three algorithms able to recognize the target gesture (mainly the human hand gesture) without carrying any device, based on just Radio Signal Strength Indicator (RSSI). Our platform utilizes only 6 telosB sensor nodes with a very easy deployment. Experiment results show that the successful recognition radio can reach around 80% in our system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.26 no.3
• /
• pp.396-402
• /
• 2022

User interactions are being developed in various forms, and in particular, interactions using human gestures are being actively studied. Among them, hand gesture recognition is used as a human interface in the field of realistic media based on the 3D Hand Model. The use of interfaces based on hand gesture recognition helps users access media media more easily and conveniently. User interaction using hand gesture recognition should be able to view images by applying fast and accurate hand gesture recognition technology without restrictions on the computer environment. This paper developed a fast and accurate user hand gesture recognition algorithm using the open source media pipe framework and machine learning's k-NN (K-Nearest Neighbor). In addition, in order to minimize the restriction of the computer environment, a stereoscopic image control system based on user hand gesture recognition was designed and implemented using a web service environment capable of Internet service and a docker container, a virtual environment.

• Proceedings of the IEEK Conference
• /
• 1998.10a
• /
• pp.1289-1292
• /
• 1998

HCI(human computer interface) technologies have been often implemented using mouse, keyboard and joystick. Because mouse and keyboard are used only in limited situation, More natural HCI methods such as speech based method and gesture based method recently attract wide attention. In this paper, we present multi-modal input system to control Windows system for practical use of multi-media computer. Our multi-modal input system consists of three parts. First one is virtual-hand mouse part. This part is to replace mouse control with a set of gestures. Second one is Windows control system using speech recognition. Third one is Windows control system using gesture recognition. We introduce neural network and HMM methods to recognize speeches and gestures. The results of three parts interface directly to CPU and through Windows.