• Journal of Digital Contents Society
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• v.13 no.1
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• pp.91-99
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• 2012

In this paper we introduce a quiz application program that digitizes the analogue quiz game. We digitize the quiz components such as quiz proceeding, participants recognition, problem presentation, volunteer recognition who raises his hand first, answer judgement, score addition, winner decision, etc, which are manually performed in the normal quiz game. For automation, we obtained the depth images from the kinect camera which comes into the spotlight recently, so that we located the quiz participants and recognized the user-friendly defined gestures. Analyzing the depth distribution, we detected and segmented the upper body parts and located the hands' areas. Also, we extracted hand features and designed the decision function that classified the hand pose into palm, fist or else, so that a participant can select the example that he wants among presented examples. The implemented quiz application program was tested in real time and showed very satisfactory gesture recognition results.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.4
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• pp.267-273
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• 2016

Hand posture recognition is an important technique to enable a natural and familiar interface in the human-computer interaction (HCI) field. This paper introduces a hand posture recognition method using a depth camera. Moreover, the hand posture recognition method is incorporated with the Moving Picture Experts Group Rich Media User Interface (MPEG-U) Advanced User Interaction (AUI) Interface (MPEG-U part 2), which can provide a natural interface on a variety of devices. The proposed method initially detects positions and lengths of all fingers opened, and then recognizes the hand posture from the pose of one or two hands, as well as the number of fingers folded when a user presents a gesture representing a pattern in the AUI data format specified in MPEG-U part 2. The AUI interface represents a user's hand posture in the compliant MPEG-U schema structure. Experimental results demonstrate the performance of the hand posture recognition system and verified that the AUI interface is compatible with the MPEG-U standard.

• Journal of the Korean Institute of Intelligent Systems
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• v.27 no.2
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• pp.126-131
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• 2017

In this paper, we propose a method to extract meaningful motion among various kinds of hand gestures on giving commands to robots using hand gestures. On giving a command to the robot, the hand gestures of people can be divided into a preparation one, a main one, and a finishing one. The main motion is a meaningful one for transmitting a command to the robot in this process, and the other operation is a meaningless auxiliary operation to do the main motion. Therefore, it is necessary to extract only the main motion from the continuous hand gestures. In addition, people can move their hands unconsciously. These actions must also be judged by the robot with meaningless ones. In this study, we extract human skeleton data from a depth image obtained by using a Kinect v2 sensor and extract location data of hands data from them. By using the Kalman filter, we track the location of the hand and distinguish whether hand motion is meaningful or meaningless to recognize the hand gesture by using the hidden markov model.

• 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.

• Journal of the HCI Society of Korea
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• v.6 no.1
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• pp.1-8
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• 2011

As virtual realty has become an issue of providing immersive services, in the area of virtual realty, it has been actively investigated to develop user interfaces for immersive interaction. In this paper, we propose a gesture recognition based immersive user interface by using an IR LED embedded helmet and data gloves in order to reflect the user's movements to the virtual reality environments effectively. The system recognizes the user's head movements by using the IR LED embedded helmet and IR signal transmitter, and the hand gestures with the data gathered from data gloves. In case of hand gestures recognition, it is difficult to recognize accurately with the general recognition model because there are various hand gestures since human hands consist of many articulations and users have different hand sizes and hand movements. In this paper, we applied the Mixture-of-Experts based gesture recognition for various hand gestures of multiple users accurately. The movement of the user's head is used to change the perspection in the virtual environment matching to the movement in the real world, and the gesture of the user's hand can be used as inputs in the virtual environment. A head mounted display (HMD) can be used with the proposed system to make the user absorbed in the virtual environment. In order to evaluate the usefulness of the proposed interface, we developed an interface for the virtual orchestra environment. The experiment verified that the user can use the system easily and intuituvely with being entertained.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2008.04a
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• pp.400-402
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• 2008

The human-computer interaction technology (HCI) that has played an important role in the exchange of information between human being and computer belongs to a key field for information technology. Recently, control studies through which robots and control devices are controlled by using the movements of a person's body or hands without using conventional input devices such as keyboard and mouse, have been going only in diverse aspects, and their importance has been steadily increasing. This study is proposing a recognition method of user's gestures by applying measurements from an acceleration sensor to the PCA algorithm.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.62-78
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• 2002

In this paper, we describe a system that can interact with agents in the virtual space incorporated in the system. This system is constructed by an analysis system for analyzing human gesture and an interact system for interacting with agents in the virtual space using analyzed information. An implemented analysis system for analyzing gesture extracts a head and hands region after taking image sequence of an operator's continuous behavior using CCD cameras. In interact system, we construct the virtual space that exist an avatar which incarnating operator himself, an autonomous object (like a Puppy), and non-autonomous objects which are table, door, window and object. Recognized gesture is transmitted to the avatar in the virtual space, then transit to next state based on state transition diagram. State transition diagram is represented in a graph in which each state represented as node and connect with link. In the virtual space, the agent link an avatar can open and close a window and a door, grab or move an object like a ball, order a puppy to do and respond to the Puppy's behavior as does the puppy.

• Archives of design research
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• v.20 no.3 s.71
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• pp.257-268
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• 2007

The development of Human Computer Interface has been relied on the development of technology. Mice and keyboards are the most popular HCI devices for personal computing. However, device-based interfaces are quite different from human to human interaction and very artificial. To develop more intuitive interfaces which mimic human to human interface has been a major research topic among HCI researchers and engineers. Also, technology in the TV industry has rapidly developed and the market penetration rate for big size screen TVs has increased rapidly. The HDTV and digital TV broadcasting are being tested. These TV environment changes require changes of Human to TV interface. A gesture recognition-based interface with a computer vision system can replace the remote control-based interface because of its immediacy and intuitiveness. This research focuses on how people use their hands or arms for command gestures. A set of gestures are sampled to control TV set up by focus group interviews and surveys. The result of this paper can be used as a reference to design a computer vision based TV interface.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.322-327
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• 2007

Researchers in the field of psychology used Electroencephalographic (EEG) to record activities of human brain lot many years. As technology develope, neural basis of functional areas of emotion processing is revealed gradually. So we measure fundamental areas of human brain that controls emotion of human by using EEG. Hands gestures such as shaking and head gesture such as nodding are often used as human body languages for communication with each other, and their recognition is important that it is a useful communication medium between human and computers. Research methods about gesture recognition are used of computer vision. Many researchers study emotion recognition method which uses one of physiological signals and gestures in the existing research. In this paper, we use together physiological signals and gestures for emotion recognition of human. And we select the driver emotion as a specific target. The experimental result shows that using of both physiological signals and gestures gets high recognition rates better than using physiological signals or gestures. Both physiological signals and gestures use Interactive Feature Selection(IFS) for the feature selection whose method is based on a reinforcement learning.

• 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.