• Journal of the Ergonomics Society of Korea
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• v.33 no.3
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• pp.175-189
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• 2014

Objective: The goal of this research is to develop new user behavior model using user motion analysis with microscopic perspective for attracting user's participation in interactive space. Background: The interactive space is 'human's place', which is made up of complex elements of digital virtual space and traditional analog and physical environment based on human-computer interaction system. Human behavior has changed in it at the same time. If the user couldn't make participation in interaction, the purpose of the system is not met, which reduces its effect. Therefore, we need to focus on interactive space that is potential future direction from a new point of view. Method: For this research, we would discuss and study fields of interactive space; (1) finding definition of interactive space and studying background of theory about it. (2) providing base of user behavior model with study of user's context that is to be user information and motion. (3) examining user motion, classify basic motion type and making user participation behavior model in phases. Results: Through this process, user's basic twenty motions which are systematized are taken as a standard for analysis of interaction process and participation in interactive space. Then, 'NK-$I^5$ (I Five)' model is developed for user participation types in interactive space. There are five phases of user participation behavior: Imperception, Interest, Involvement, Immersion, and Influence. In this analysis, three indicators which are time, motion types, and user relationship are found to be related to participation. Conclusion: The capabilities and limitation of this research is discussed to attract user participation. This paper focuses especially on contribution of design to lead user's participation in interactive system and expectation to help adapt to user centered design of various interactive space with new aspect of user behavior research. Application: The results of the 'NK-$I^5$ (I Five)' model might help to realize successful interactive space based on user centered design.

• Journal of Digital Contents Society
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• v.17 no.6
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• pp.531-536
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• 2016

This study highlights the effectiveness of analyzing the feelings children have when interacting with robots in a dramatic play setting using augmented reality in Human Robot Interaction (HRI). Existing dramatic play activities using robots by QR-markers were edited, and their weaknesses have been corrected so that children could interact more effectively with robots. Additionally, children's levels of interest and engagement in dramatic play activities, the accuracy of robotic props, and the smartness of robots were analyzed throughout children's interactions during such activities using augmented reality. Younger participants were more likely to find robots interesting and intelligent, and participants with no previous experience with robots had relatively higher levels of interest in robots and tended to notice changes in robots' costumes.

• Journal of the Korea Computer Graphics Society
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• v.10 no.2
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• pp.1-9
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• 2004

본 논문에서는 바이러스와 같은 생화학 물질의 분자구조를 3 차원 모델로 시각화하여 관찰하고, 그 분자모델을 직관적인 방법으로 조작하기 위한 가상 현실 분자 모델링 시스템을 제안한다. 이 시스템을 사용하면, 입체영상 디스플레이 장치와 데이터 글러브 및 동작 추적 장치를 사용하여 3 차원 분자 모델을 실감나게 조작할 수 있어서 효율적으로 분자들을 관찰하고 결합, 분리하는 등의 분자 모델링 작업이 가능하다. 사용자들은 마우스나 키보드 등의 장비 대신에 자연스러운 몸 동작이나 손 동작을 이용하여 분자 모델링 작업을 위한 동작을 하게 된다. 분자들의 결합을 화학적으로 정확하게, 그리고 실시간으로 시뮬레이션 하기 위해서 에너지 계산 알고리즘을 구현하였으며 이러한 작업이 가능하도록 분자 구조를 표현하는 새로운 자료구조를 제안하였다. 본 연구에서 제안하는 동작 기반의 VR 분자 모델링 시스템의 타당성을 검증하기 위하여 HIV 바이러스 분자를 가지고 분자 모델링 작업을 수행하였고, 사용자 테스트를 실시하여 기존의 방식과 작업 성능 및 사용자 만족도를 비교하였다.

• Journal of the Korean Data and Information Science Society
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• v.15 no.4
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• pp.817-823
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• 2004

This paper describes a three dimensional motion recognition algorithm and a system which adopts the algorithm for non-contact human-computer interaction. From sequence of stereos images, five feature regions are extracted with simple color segmentation algorithm and then those are used for three dimensional locus calculation precess. However, the result is not so stable, noisy, that we introduce principal component analysis method to get more robust motion recognition results. This method can overcome the weakness of conventional algorithms since it directly uses three dimensional information motion recognition.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2930-2932
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• 2000

In this paper. a robust gesture recognition system is designed and implemented to explore the communication methods between human and computer. Hand gestures in the proposed approach are used to communicate with a computer for actions of a high degree of freedom. The user does not need to wear any cumbersome devices like cyber-gloves. No assumption is made on whether the user is wearing any ornaments and whether the user is using the left or right hand gestures. Image segmentation based upon the skin-color and a shape analysis based upon the invariant moments are combined. The features are extracted and used for input vectors to a radial basis function networks(RBFN). Our "Puppy" robot is employed as a testbed. Preliminary results on a set of gestures show recognition rates of about 87% on the a real-time implementation.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1728-1735
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• 2009

Human action tracking plays an important place in human-computer-interaction, human action tracking is a challenging task because of the exponentially increased computational complexity in terms of the degrees of freedom of the object and the severe image ambiguities incurred by frequent self-occlusions. In this paper, we will propose a novel method to track human action, in our technique, a dynamic background estimation algorithm will be applied firstly. Based on the estimated background, we then extract the human object from the video sequence, and the skeletonization method and Hough transform method will be used to detect the main structure of human body and each part rotation angle. The calculated rotation angles will be used to control a crane in the port, thus we can just control the container crane by using signalman body. And the experimental results can show that our proposed method can get a preferable result than the conventional methods such as: MIT, JPF or MFMC.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.411-417
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• 2021

The field that studies human-computer interaction is called HCI (Human-computer interaction). This field is an academic field that studies how humans and computers communicate with each other and recognize information. This study is a study on hand gesture recognition for human interaction. This study examines the problems of existing recognition methods and proposes an algorithm to improve the recognition rate. The hand region is extracted based on skin color information for the image containing the shape of the human hand, and the center of gravity profile is calculated using principal component analysis. I proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. We proposed a method to increase the recognition rate of hand gestures by comparing the obtained information with predefined shapes. The existing center of gravity profile has shown the result of incorrect hand gesture recognition for the deformation of the hand due to rotation, but in this study, the center of gravity profile is used and the point where the distance between the points of all contours and the center of gravity is the longest is the starting point. Thus, a robust algorithm was proposed by re-improving the center of gravity profile. No gloves or special markers attached to the sensor are used for hand gesture recognition, and a separate blue screen is not installed. For this result, find the feature vector at the nearest distance to solve the misrecognition, and obtain an appropriate threshold to distinguish between success and failure.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.559-575
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• 2023

3D human pose estimation is widely applied in various fields, including action recognition, sports analysis, and human-computer interaction. 3D human pose estimation has achieved significant progress with the introduction of convolutional neural network (CNN). Recently, several researches have proposed the use of multiview approaches to avoid occlusions in single-view approaches. However, as the number of cameras increases, a 3D pose estimation system relying on a CNN may lack in computational resources. In addition, when a single host system uses multiple cameras, the data transition speed becomes inadequate owing to bandwidth limitations. To address this problem, we propose a distributed real-time 3D pose estimation framework based on asynchronous multiple cameras. The proposed framework comprises a central server and multiple edge devices. Each multiple-edge device estimates a 2D human pose from its view and sendsit to the central server. Subsequently, the central server synchronizes the received 2D human pose data based on the timestamps. Finally, the central server reconstructs a 3D human pose using geometrical triangulation. We demonstrate that the proposed framework increases the percentage of detected joints and successfully estimates 3D human poses in real-time.

• Journal of Computing Science and Engineering
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• v.9 no.1
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• pp.29-38
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• 2015

Human action recognition has become an important research topic in computer vision area recently due to many applications in the real world, such as video surveillance, video retrieval, video analysis, and human-computer interaction. The goal of this paper is to evaluate descriptors which have recently been used in action recognition, namely Histogram of Oriented Gradient (HOG) and Histogram of Optical Flow (HOF). This paper also proposes new descriptors to represent the change of points within each part of a human body, caused by actions named as Histogram of Changing Points (HCP) and so-called Average Speed (AS) which measures the average speed of actions. The descriptors are combined to build a strong descriptor to represent human actions by modeling the information about appearance, local motion, and changes on each part of the body, as well as motion speed. The effectiveness of these new descriptors is evaluated in the experiments on KTH and Hollywood datasets.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.4 no.3
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• pp.202-208
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• 2011

Recently the technologies that control the computer system through human computer interaction(HCI) have been widely studied. Their applications usually involve the methods that locate user's positions via face detection and recognize user's gestures, but face detection performance is not good enough. In case that the applications do not locate user's position stably, user interface performance, such as gesture recognition, is significantly decreased. In this paper we propose a new stable face detection algorithm using skin color detection and cumulative distribution of face detection results, whose effectiveness was verified by experiments. The propsed algorithm can be applicable in the area of human tracking that uses correspondence matrix analysis.