• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.140-142
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• 2000

인간과 기계가 효과적인 상호작용을 하기 위해서는 컴퓨터 시스템이 인간의 행동을 인식할 수 있어야 한다. 본 연구에서는 인공 신경망을 사용하여 컴퓨터 시스템이 인간의 움직임을 관찰한 후 행위자의 성별을 인식하도록 하는 시스템을 구현하였다. 두 가지 감정상태(보통상태, 화난 상태) 하에서 일어난 인간의 세 가지 동작(문 두드리기, 손 흔들기, 물건 들어올리기)을 대상으로 하여 인간 동작 데이터를 통해 만들어진 학습 데이터를 통해 98.0%의 인식률을 보일 때까지 학습시키고 나서, 이전에 사용하지 않았던 새로운 데이터에 대해 얼마나 설별을 잘 구별해 내는지 실험하였다. 동작이 일어나는 동안 행위자의 몸 여섯 군데에서 속도 데이터를 얻어내서 신경망의 입력값으로 사용하였다. 그 결과 최저 62.3%이상 최고 94.3%까지 인간 성별을 구분해 낼 수 있었고 이는 같은 데이터에 대해서 사람을 통해 실험한 것보다 훨씬 나은 것이다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.4 s.304
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• pp.11-18
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• 2005

For expressing intention the human often use body languages as well as vocal languages. Of course the gestures using arms and hands are the representative ones among the body languages. Therefore it is very important to understand the human arm motion in human-computer interaction. In this respect we present here how to estimate 3D pose of human arms by using computer vision systems. For this we first focus on the idea that the human arm motion consists of mostly revolute joint motions, and then we present an algorithm for understanding 3D motion of a revolute joint using vision systems. Next we apply it to estimating 3D pose of human arms using vision systems. The fundamental idea for this algorithm extension is that we may apply the algorithm for a revolute joint to each of the revolute joints of hmm arms one after another. In designing the algorithms we focus on seeking closed-form solutions with high accuracy because we aim at applying them to human computer interaction for ubiquitous computing and virtual reality.

• Journal of Advanced Navigation Technology
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• v.24 no.2
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• pp.155-162
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• 2020

Recently, with the development of computer vision and deep learning technology, research on human action recognition has been actively conducted for video analysis, video surveillance, interactive multimedia, and human machine interaction applications. Diverse techniques have been introduced for human action understanding and classification by many researchers using RGB image, depth image, skeleton and inertial data. However, skeleton-based action discrimination is still a challenging research topic for human machine-interaction. In this paper, we propose an end-to-end skeleton joints mapping of action for generating spatio-temporal image so-called dynamic image. Then, an efficient deep convolution neural network is devised to perform the classification among the action classes. We use publicly accessible UTD-MHAD skeleton dataset for evaluating the performance of the proposed method. As a result of the experiment, the proposed system shows better performance than the existing methods with high accuracy of 97.45%.

• Proceedings of the Korea Contents Association Conference
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• 2009.05a
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• pp.915-920
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• 2009

In terms of development of intelligent information devices, the most important element is the function which is able to deliver the information user wants to input on the device without complexities. By using the mean such as our voice, expression, gesture and physical contact we use in our daily routine, we are able to interact with device easily and simply. In this paper, we are initiated to present interactive surface system, in which allows users to use their hand gesture as a function of mouse and keyboard free, to be interacted within the platform of web application.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.11
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• pp.7508-7512
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• 2015

We propose a brain-machine interface(BMI) based human-robot interaction(HRI) platform which operates machines by interfacing intentions by capturing brain waves. Platform consists of capture, processing/mapping, and action parts. A noninvasive brain wave sensor, PC, and robot-avatar/LED/motor are selected as capture, processing/mapping, and action part(s), respectively. Various investigations to ensure the relations between intentions and brainwave sensing have been explored. Case studies-an interactive game, on-off controls of LED(s), and motor control(s) are presented to show the design and implementation process of new BMI based HRI platform.

• The Journal of the Convergence on Culture Technology
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• v.7 no.1
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• pp.145-150
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• 2021

This thesis attempted to examine the mechanization of humans, humanization of machines, and coexistence through dance works. The dance works were reviewed by partial excerpts from Oscar Schlemer's <3 Chord Ballet>, Felindrome Dance Company's , and . Also, I looked at the dance work , which has an inherent form of coexistence. Through the above work, robot-like science and technology and fusion. It was found that various dance performances that coexist in complex forms provide continuous creativity to humans, and various forms of sensibility and creative movements based on data make it possible to produce rich performances for humans. This researcher expects numerous works that accept and reflect the changes of the times through the embodied interaction of dance performances with science and technology.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.10
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• pp.980-984
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• 2010

Exploring microRNA (miRNA) and mRNA regulatory interactions may give new insights into diverse biological phenomena. Recently, miRNAs have been discovered as important regulators that play a major role in various cellular processes. Therefore, it is essential to identify functional interactions between miRNAs and mRNAs for understanding the context- dependent activities of miRNAs in complex biological systems. While elucidating complex miRNA-mRNA interactions has been studied with experimental and computational approaches, it is still difficult to infer miRNA-mRNA regulatory modules. Here we present a novel method, termed layered hypernetworks (LHNs), for identifying functional miRNA-mRNA interactions from heterogeneous expression data. In experiments, we apply the LHN model to miRNA and mRNA expression profiles on multiple cancers. The proposed method identifies cancer-specific miRNA-mRNA interactions. We show the biological significance of the discovered miRNA- mRNA interactions.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.901-904
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• 2020

본 시스템은 세 단계의 모델을 복합적으로 구성하여 이루어진다. 첫 단계로 사람의 음성언어를 텍스트로 전환한 후 사용자의 발화 의도를 분류해내는 BoW방식을 이용해 인간의 명령을 이해할 수 있는 자연어 처리 알고리즘을 구성한다. 이후 YOLOv3-tiny를 이용한 실시간 영상처리모델과 OctoMapping모델을 활용하여 주변환경에 대한 3차원 지도생성 후 지도데이터를 기반으로하여 동작하는 기구제어 알고리즘 등을 ROS actionlib을 이용한 관리자시스템을 구성하여 ROS와 딥러닝을 활용한 편리한 인간-로봇 상호작용 시스템을 제안한다.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.8
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• pp.870-877
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• 2013

There has been much recent research interest in developing numerous kinds of human-machine interface. This field currently requires more accurate and reliable sensing systems to detect the intended human motion. Most conventional human-machine interface use electromyography (EMG) sensors to detect the intended motion. However, EMG sensors have a number of disadvantages and, as a consequence, the human-machine interface is difficult to use. This study describes a muscle volume sensor (MVS) that has been developed to measure variation in the outline of a muscle, for use as a human-machine interface. We developed an algorithm to calibrate the system, and the feasibility of using MVS for detecting muscular activity was demonstrated experimentally. We evaluated the performance of the MVS via isotonic contraction using the KIN-COM$^{(R)}$ equipment at torques of 5, 10, and 15 Nm.

• Journal of The Korean Association of Information Education
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• v.3 no.1
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• pp.13-21
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• 1999

'Interactivity' is considered as a key factor of user-centered interactive instructional systems design in Web environments. To provide an optimal level of interactivity for learners is an ideal goal in instructional systems design(ISD) process. Based on the primary concern of interactive systems design which pursues how the power of interactivity can be utilized and put to work, several interactive design strategies in Web-based systems are recommended through this research.