• 디자인학연구
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• 제13권1호
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• pp.139-148
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• 2000

디지털 기술의 발전으로 컴퓨터와 정보 통신 기술이 결합하여 하나의 시스템에서 다매체 즉 인터그레이티드 미디어(Integrated media)를 가능케 하였다. 인터그레이티드 미디어는 통합적 미디어에 의한 정보 전달방법으로 인간의 정보 전달 체계와 가장 유사한 형태로 발전되어 왔다. 따라서 인터페이스 분야에서도 형태적인 발전에 따라 인간과 컴퓨터의 상호작용(Human Computer Interaction)이라는 중요한 테마로 발전하였다. 인터페이스의 형태적 발전은 디자인 분야에서도 재정립되고 있지만 많은 분야의 동시 접목과 제품개발에 있어 체계성 부족으로 활용이 지체되고 있다. 본 연구는 MP3 자판기 개발 사례를 바탕으로 정보전달 형태 개발을 위한 요소들을 재구성함으로써 인터페이스의 새로운 모델을 구축하기 위한 시도이다. 체계적인 분류를 위하여 인터페이스를 인지적인 면과 조형적인 면을 분류하고, 하드웨어와 소프트웨어로 분류하여 누구나 쉽게 이해할 수 있도록 정립하였으며, 결과적으로 새로운 통합적 인터페이스(Integrated Interface)의 패러다임(Paradigm)을 제시함으로써 디자인의 새로운 방향 즉 통합적 아이덴티티를 구축을 위한 기본 틀을 제시하였다.

• 반도체디스플레이기술학회지
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• 제16권4호
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• pp.79-85
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• 2017

Understanding of human emotion has a high importance in interaction between human and machine communications systems. The most expressive and valuable way to extract and recognize the human's emotion is by facial expression analysis. This paper presents and implements an automatic extraction and recognition scheme of facial expression and emotion through still image. This method has three main steps to recognize the facial emotion: (1) Detection of facial areas with skin-color method and feature maps, (2) Creation of the Bezier curve on eyemap and mouthmap, and (3) Classification and distinguish the emotion of characteristic with Hausdorff distance. To estimate the performance of the implemented system, we evaluate a success-ratio with emotional face image database, which is commonly used in the field of facial analysis. The experimental result shows average 76.1% of success to classify and distinguish the facial expression and emotion.

• Transactions on Control, Automation and Systems Engineering
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• 제4권1호
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• pp.38-42
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• 2002

Conditions are discussed for operating a dissymmetric human master-small (or micro) slave system in best (large position gain-small velocity gain) conditions allowing higher operator dexterity when real effects (joint compliance, link flexion delay and transmission distortion) are taken into account. It is shown that position PD feedback law advantage for ideal case no longer holds, and that more complicated feedback law depending on real effects has to be implemented with adapted transmission line. Drawback is slowdown of master slave interaction, suggesting to use more advanced predictive methods for the master and more intelligent control law for the slave.

• Journal of Multimedia Information System
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• 제3권2호
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• pp.9-12
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• 2016

This paper is concerned with the effective and efficient identification of the gender and motion of humans. Tracking this nonverbal behavior is useful for providing clues about the interaction of different types of people and their exact motion. This system can also be useful for security in different places or for monitoring patients in hospital and many more applications. Here we describe a novel method of determining identity using machine learning with Microsoft Kinect. This method minimizes the fitting or overlapping error between an ellipsoid based skeleton.

• 산업경영시스템학회지
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• 제17권30호
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• pp.25-34
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• 1994

Mental workload has a improtant place in modern work environment such as human-computer interaction. Designing man-machine system requires knowledge and evaluation of the human cognitive process which controls information flow during our works. Many studies estimate reaction time as a index of menatal workload. This paper investigates what reflacts the workload of human information handling when the informations grow its degree. Experiment result introuce the memory time that explain the information-load more sensitive than react time. And react time shows learning effect but memory time does'nt show that effect So it can be concluded that cognitive learning or work schema needs more time to achieve dexterity than motor skill.

• 융합정보논문지
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• 제9권8호
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• pp.1-8
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• 2019

대화시스템은 인간과 컴퓨터의 상호작용에 새로운 패러다임이 되고 있다. 자연어로써 상호작용함으로써 인간은 보다 자연스럽고 편리하게 각종 서비스를 누릴 수 있게 되었다. 대화시스템의 구조는 일반적으로 음성 인식, 자연어 이해, 문맥 파악 등의 여러 모듈의 파이프라인으로 이뤄지는데, 본 연구에서는 자연어 이해 모듈의 도메인 분류 문제를 풀기 위해 convolutional neural network, random forest 등의 기계학습 모델을 비교하였다. 사람이 직접 태깅한 총 7개 서비스 도메인 데이터에 대하여 각 문장의 도메인을 분류하는 실험을 수행하였고 random forest 모델이 F1 score 0.97 이상으로 가장 높은 성능을 달성한 것을 보였다. 향후 다른 기계학습 모델들을 추가 실험함으로써 도메인 분류 성능 개선을 지속할 계획이다.

• 한국CDE학회논문집
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• 제12권2호
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• pp.126-136
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• 2007

Teleconferences have been used in business sectors to reduce traveling costs. Traditionally, specialized telephones that enabled multiparty conversations were used. With the introduction of high speed networks, we now have high definition videos that add more realism in the presence of counterparts who could be thousands of miles away. This paper presents a new technology that adds even more realism by telecommunicating with hand gestures. This technology is part of a teleconference system named SMS (Smart Meeting Space). In SMS, a person can use hand gestures to manipulate meeting data that could be in the form of text, audio, video or 3D shapes. Fer detecting hand gestures, a machine learning algorithm called SVM (Support Vector Machine) has been used. For the prototype system, a 3D interaction environment has been implemented with $OpenGL^{TM}$, where a 3D human skull model can be grasped and moved in 6-DOF during a remote conversation between distant persons.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.40-48
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• 2023

Speech Emotions recognition has become the active research theme in speech processing and in applications based on human-machine interaction. In this work, our system is a two-stage approach, namely feature extraction and classification engine. Firstly, two sets of feature are investigated which are: the first one is extracting only 13 Mel-frequency Cepstral Coefficient (MFCC) from emotional speech samples and the second one is applying features fusions between the three features: Zero Crossing Rate (ZCR), Teager Energy Operator (TEO), and Harmonic to Noise Rate (HNR) and MFCC features. Secondly, we use two types of classification techniques which are: the Support Vector Machines (SVM) and the k-Nearest Neighbor (k-NN) to show the performance between them. Besides that, we investigate the importance of the recent advances in machine learning including the deep kernel learning. A large set of experiments are conducted on Surrey Audio-Visual Expressed Emotion (SAVEE) dataset for seven emotions. The results of our experiments showed given good accuracy compared with the previous studies.

• International Journal of Advanced Culture Technology
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• 제11권1호
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• pp.389-394
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• 2023

Based on intelligent visual information and 5G, this paper studies the intelligent visual communication of landscape bamboo buildings, and provides a new method of intelligent perception and interactive computing for the real world, which can represent, model, Perception and cognition; through the integration of virtual and real, the situational understanding of the human-machine-material fusion environment and the interaction with nature. The 5G network can well meet the combination of high-bandwidth uplink transmission and low-latency downlink control. At the same time, 5G-based AR intelligent inspection, remote operation and maintenance guidance, and machine vision inspection. Taking the bamboo building as an example, through field inspections to analyze tourism Bamboo buildings before and after development, and the intelligentization of bamboo buildings based on 5G and visual modeling.

• 한국차세대컴퓨팅학회논문지
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• 제15권3호
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• pp.16-24
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• 2019

최근 뇌파를 기반으로 한 인간의 감정을 인식하는 연구가 인간-로봇 상호작용 분야에서 활발히 진행되고 있다. 본 논문에서는 MAHNOB-HCI에서 사용된 자기평가와 주석 레이블링 방법과는 다른, 이미지 기반의 뇌파 Topography를 이용한 레이블링을 통해 감정을 평가하는 방법을 제안한다. 제안한 방법은 뇌파 신호를 Topography의 이미지로 변환하여 기계학습 모델을 학습하고 이를 기반으로 Valence 기반의 감정을 평가한다. 제안한 방법은 레이블링 과정을 자동화하여 지연 시간을 없애고 객관적인 레이블링을 제공할 수 있다. MAHNOB-HCI 데이터베이스를 적용한 실험에서 SVM, kNN의 기계학습 모델을 학습하여 주석 레이블링과 성능 비교를 하였으며, 제안 방법의 감정인식 정확도를 SVM에서 54.2%, kNN에서 57.7%로 확인하였다.