• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.6063-6079
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• 2019

When the length of sampling data sequence is too large, the method of gesture recognition based on traditional Dynamic Time Warping (DTW) algorithm will lead to too long calculation time, and the accuracy of recognition result is not high.Support vector machine (SVM) has some shortcomings in precision, Edit Distance on Real Sequences(EDR) algorithm does not guarantee that noise suppression will not suppress effective data.A new method based on Improved Interpolation Dynamic Time Warping (IIDTW)algorithm is proposed to improve the efficiency of gesture recognition and the accuracy of gesture recognition. The results show that the computational efficiency of IIDTW algorithm is more than twice that of SVM-DTW algorithm, the error acceptance rate is FAR reduced by 0.01%, and the error rejection rate FRR is reduced by 0.5%.Gesture recognition based on IIDTW algorithm can achieve better recognition status. If it is applied to unlock mobile phone, it is expected to become a new generation of unlock mode.

• Journal of Information Processing Systems
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• v.20 no.3
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• pp.328-336
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• 2024

Visual communication is widely used and enhanced in modern society, where there is an increasing demand for spirituality. Museum robots are one of many service robots that can replace humans to provide services such as display, interpretation and dialogue. For the improvement of museum guide robots, the paper proposes a human-robot interaction system based on visual communication skills. The system is based on a deep neural mesh structure and utilizes theoretical analysis of computer vision to introduce a Tiny+CBAM mesh structure in the gesture recognition component. This combines basic gestures and gesture states to design and evaluate gesture actions. The test results indicated that the improved Tiny+CBAM mesh structure could enhance the mean average precision value by 13.56% while maintaining a loss of less than 3 frames per second during static basic gesture recognition. After testing the system's dynamic gesture performance, it was found to be over 95% accurate for all items except double click. Additionally, it was 100% accurate for the action displayed on the current page.

• Korea Science and Art Forum
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• v.20
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• pp.307-314
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• 2015

Tele-Gesture is a tangible user interface(TUI) device that allows a user to physically point to a 3D object in real life and have their gestures play back by a robotic finger that can point to the same object, either at the same time, or at another point in time. To understand the extent of the gestures as new way of digital collaborative communication, collaboration situation and types were experimented as TUI implementations. The design prototype reveals that there is a rich non-verbal component of communication in the form of gesture-clusters and body movements that happen in an digital communication. This result of analysis can contribute to compile relevant contributions to the fields of communication, human behavior, and interaction with high technology through an interpretive social experience.

• Smart Media Journal
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• v.11 no.6
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• pp.30-36
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• 2022

This paper explored the effect of using eye gaze pointer in addition to the hand gesture visual communication cue in remote collaboration. We recruited 24 participants and conducted a user study comparing two conditions: (1) only hand gesture visual communication cue, and (2) eye gaze pointer with hand gesture visual cue. The results showed that the added eye gaze pointer cue reduced the workload and increased the co-presence when using it together with hand gesture cue.

• Journal of Korean Elementary Science Education
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• v.31 no.4
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• pp.450-462
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• 2012

Gestures are a common phenomenon of human communication. There exists little research concerned with the gestures in science education, and most researches of gestures have focused on individual gestures. However, learning occurs through sociocultural interactions with friends, family, teachers, and others in society. Hence, the purpose of this study was to investigate and identify the types and features of gestures which were made by elementary students to communicate with peers in science discourse. A group of six fourth-graders was observed in eight science discourses where they talked about ideas related to thermal concepts. The data was collected through interviews and questionnaires. The analysis of the data showed that students' gestures in science discourses could be classified into seven types: signal iconic gesture, illustrative iconic gesture, personal deictic gesture, object deictic gesture, beat gesture, emotional metaphoric gesture, and content metaphoric gesture. It was also found that these gestures had functions of repeating, supplementing, and replacing utterance to communicate with others. Students frequently expressed scientific terms metaphorically as everyday terms through their gestures. Gestures were shared, imitated, and transferred in the communication process, and students' gestures also made influence on other students' ideas through these processes.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1393-1402
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• 2013

Hand gesture is one of the most popular communication methods in everyday life. In human-computer interaction applications, hand gesture recognition provides a natural way of communication between humans and computers. There are mainly two methods of hand gesture recognition: glove-based method and vision-based method. In this paper, we propose a vision-based hand gesture recognition method using Kinect. By using the depth information is efficient and robust to achieve the hand detection process. The finger labeling makes the system achieve pose classification according to the finger name and the relationship between each fingers. It also make the classification more effective and accutate. Two kinds of gesture sets can be recognized by our system. According to the experiment, the average accuracy of American Sign Language(ASL) number gesture set is 94.33%, and that of general gestures set is 95.01%. Since our system runs in real-time and has a high recognition rate, we can embed it into various applications.

• The Journal of the Korea Contents Association
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• v.11 no.3
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• pp.179-189
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• 2011

Gesture is one of the means for non-linguistic communication which can be expressed by human characters in animations. High drawing ability and profound knowledge about gestures are both required for animators to achieve efficient gesture expressions. However, diversified profound techniques are needed to master this knowledge which makes it very difficult for common animation drawers. In this paper, characteristics for each gesture are analyzed based on Laban Movement Analysis and gesture classification by making gesture packets. This research is of notable significance in providing animators with high efficient gesture expression techniques and developing automatic gesture-generating system.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.121-127
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• 2005

There is a necessity for the communication between intelligent robots and human beings because of wide spread use of them. Gesture recognition is currently being studied in regards to better conversing. On the basis of previous research, however, the gesture recognition algorithms appear to require not only complicated algorisms but also separate training process for high recognition rates. This study suggests a gesture recognition algorithm based on computer vision system, which is relatively simple and more efficient in recognizing various human gestures. After tracing the hand gesture using a marker, direction changes of the gesture trajectory were analyzed to determine the simple gesture code that has minimal information to recognize. A map is developed to recognize the gestures that can be expressed with different gesture codes. Through the use of numerical and geometrical trajectory, the advantages and disadvantages of the suggested algorithm was determined.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.143-149
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• 2019

Floating holograms are technologies that provide rich 3D stereoscopic images in a wide space such as advertisement, concert. In addition, It is possible to reduce the 3D glasses inconvenience, eye strain, and space distortion, and to enjoy 3D images with excellent realism and existence. Therefore, this paper implements a user gesture recognition system for manipulating a floating hologram characters that can be used in a small space devices. The proposed method detects face region using haar feature-based cascade classifier, and recognizes the user gestures using a user gesture-occurred position information that is acquired from the gesture difference image in real time. And Each classified gesture information is mapped to the character motion in floating hologram for manipulating a character action. In order to evaluate the performance of the proposed user gesture recognition system for manipulating a floating hologram character, we make the floating hologram display devise, and measures the recognition rate of each gesture repeatedly that includes body shaking, walking, hand shaking, and jumping. As a results, the average recognition rate was 88%.

• The Journal of the Korea Contents Association
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• v.5 no.4
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• pp.122-132
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• 2005

CVE(Collaborative Virtual Environment) is the virtually shared area where people cannot come together physically, but wish to discuss, collaborate on, or even dispute certain matters. In CVEs, in habitants are usually represented by humanoid embodiments, generally referred to as avatars. But most current graphical CVE systems fail to reflect the natural relationship between the avatar's gesture and the conversation that is taking place. More than 65% of the information exchanged during a person to person conversation is carried on the nonverbal band. Therefore, it is expected to be beneficial to provide such communication channels in CVEs in some way. To address this issue, this study proposes a scheme to represent avatar's gestures that can support the CVE users' communication. In the first level, this study classifies the non-verbal communication forms that can be applicable to avatar gesture design. In the second level, this study categorizes the body language according to the types of interaction with verbal language. And in the third level, this study examines gestures with relevant verbal expressions according to the body parts-from head to feet. One bodily gesture can be analyzed in the description of gesture representation, the meaning of gesture and the possible expressions, which can be used in gestural situation.