• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.321-322
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• 2007

본 논문에서는 로봇과 인간의 인터액션을 위해 인간 몸의 실루엣 및 액티브 스켈레톤 추출 기법을 제안한다. 연속된 이미지 정보로 부터 얻어진 옷영역등의 정보에서 background subtraction를 이용한 adaptive fusion을 통해 추출된 인간 몸의 실루엣을 바탕으로 active contour와 가상 신체 모델인 skeleton model을 응용하여 작은 움직임에 보다 강한 active skeleton model을 이용하여 인간 몸의 특징 점 위치를 추출하는 방법을 한다.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.211-223
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• 2024

Chatbots have become very popular in our times and are used in several fields. The emergence of chatbots has created a new way of communicating between human and computer interaction. A Chatbot also called a "Chatter Robot," or conversational agent CA is a software application that mimics human conversations in its natural format, which contains textual material and oral communication with artificial intelligence AI techniques. Generally, there are two types of chatbots rule-based and smart machine-based. Over the years, several chatbots designed in many languages for serving various fields such as medicine, entertainment, and education. Unfortunately, in the Arabic chatbots area, little work has been done. In this paper, we developed a beneficial tool (chatBot) in the Arabic language which contributes to educating people about the Prophet's biography providing them with useful information by using Natural Language Processing.

• Journal of the Korean Institute of Intelligent Systems
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• v.23 no.6
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• pp.565-570
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• 2013

The mirror neuron regions which are distributed in cortical area handled a functionality of intention recognition on the basis of imitative learning of an observed action which is acquired from visual-information of a goal-directed action. In this paper an automated intention recognition system is proposed by applying computational model of mirror neuron system to the human-robot interaction system. The computational model of mirror neuron system is designed by using dynamic neural networks which have model input which includes sequential feature vector set from the behaviors from the target object and actor and produce results as a form of motor data which can be used to perform the corresponding intentional action through the imitative learning and estimation procedures of the proposed computational model. The intention recognition framework is designed by a system which has a model input from KINECT sensor and has a model output by calculating the corresponding motor data within a virtual robot simulation environment on the basis of intention-related scenario with the limited experimental space and specified target object.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.5
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• pp.486-494
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• 2014

Intelligent homes consist of ubiquitous sensors, home networks, and a context-aware computing system. These homes are expected to offer many services such as intelligent air-conditioning, lighting control, health monitoring, and home security. In order to realize these services, many researchers have worked on various research topics including smart sensors with low power consumption, home network protocols, resident and location detection, context-awareness, and scenario and service control. This paper presents the real-time metabolic rate estimation method that is based on measured heart rate for human adaptive appliance (air-conditioner, lighting etc.). This estimation results can provide valuable information to control smart appliances so that they can adjust themselves according to the status of residents. The heart rate based method has been experimentally compared with the location-based method on a test bed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.11
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• pp.1496-1505
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• 2018

The technology of emotion recognition is necessary for human computer interaction communication. There are many cases where one cannot communicate without considering one's emotion. As such, emotional recognition technology is an essential element in the field of communication. n this regard, it is highly utilized in various fields. Various bio-sensor sensors are used for human emotional recognition and can be used to measure emotions. This paper proposes a system for recognizing human emotions using two physiological sensors. For emotional classification, two-dimensional Russell's emotional model was used, and a method of classification based on personality was proposed by extracting sensor-specific characteristics. In addition, the emotional model was divided into four emotions using the Support Vector Machine classification algorithm. Finally, the proposed emotional recognition system was evaluated through a practical experiment.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.1
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• pp.46-51
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• 2007

This paper is to present gesture analysis for human-robot interaction. Understanding human emotions through gesture is one of the necessary skills fo the computers to interact intelligently with their human counterparts. Gesture analysis is consisted of several processes such as detecting of hand, extracting feature, and recognizing emotions. For efficient operation we used recognizing a gesture with HMM(Hidden Markov Model). We constructed a large gesture database, with which we verified our method. As a result, our method is successfully included and operated in a mobile system.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.5
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• pp.144-149
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• 2013

With the increasing of service robots, human-robot interaction for natural communication between user and robots is becoming more and more important. Especially, face recognition is a key issue of HRI. Even though robots mainly use face detection and recognition to provide various services, it is still difficult to guarantee of performance due to insufficient test methods in real service environment. Now, face recognition performance of most robots is evaluation for engine without consideration for robots. In this paper, we show validity of test method using LED monitor through performance comparison of real images with from images LED monitor.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3037-3040
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• 2000

Real-Time object tracking has emerged as an important component in several application areas including machine vision. surveillance. Human-Computer Interaction. image-based control. and so on. And there has been developed various algorithms for a long time. But in many cases. they have showed limited results under uncontrolled situation such as illumination changes or cluttered background. In this paper. we present a novel. computationally efficient algorithm for tracking human face robustly under illumination changes and cluttered backgrounds. Previous algorithms usually defines color model as a 2D membership function in a color space without consideration for illumination changes. Our new algorithm developed here. however. constructs a 3D color model by analysing plenty of images acquired under various illumination conditions. The algorithm described is applied to a mobile head-eye robot and experimented under various uncontrolled environments. It can track an human face more than 100 frames per second excluding image acquisition time.

• Journal of Fashion Business
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• v.25 no.6
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• pp.119-130
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• 2021

This study investigated the effects of the chatbot's level of anthropomorphism - closeness to the human form - and its self-disclosure - delivery of emotional exchange with the chatbot through its facial expressions and chatting message on the user's intention to accept the service. A 2 (anthropomorphism: High vs. Low) × 2 (self-disclosure through facial expressions: High vs. Low) × 2 (self-disclosure through conversation: High vs. Low) between-subject factorial design was employed for this study. An online survey was conducted and a total of 234 questionnaires were used in the analysis. The results showed that consumers used chatbot service more when emotions were disclosed through facial expressions, than when it disclosed fewer facial expressions. There was statistically significant interaction effect, indicating the relationship between chatbot's self-disclosure through facial expression and the consumers' intention to use chatbot service differs depending on the extent of anthropomorphism. In the case of "robot chatbots" with low anthropomorphism levels, there was no difference in intention to use chatbot service depending on the level of self-disclosure through facial expression. When the "human-like chatbot" with high anthropomorphism levels discloses itself more through facial expressions, consumer's intention to use the chatbot service increased much more than when the human-like chatbot disclosed fewer facial expressions. The findings suggest that chatbots' self-disclosure plays an important role in the formation of consumer perception.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.339-346
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• 2006

최근 들어 유치원과 초등학교에 로봇을 이용한 교육적 활용 연구가 시도되고 있다. 유비퀴터스 로봇 활용이 교사와 아동의 흥미 유발에 있어 매우 효과가 높은 것으로 나타나, 향후 유비쿼터스 로봇이 u-Learning 의 또 다른 매체로서의 가능성이 강조되고 있다. 이에 본 연구에서는 초등학교 수업에서 교사 보조 역할을 통한 유비퀴터스 로봇의 활용 가능성을 보기 위해, 초등 학생 6 학년의 기대 역할을 갖는 프로토 타입의 로봇과 컨텐츠를 개발하여 활용하는 실험을 실시하였다. 프로토 타입 로봇은 국어, 영어, 음악 교과를 대상으로 주기적으로 컨텐츠를 다운로드 할 수 있을 뿐만 아니라 아동의 얼굴과 이름을 저장하여 수업 운영 컨텐츠와 연동할 수 있다. 현장 실험을 통하여 아동이 유비쿼터스 로봇을 경험한 수업 시간의 횟수에 따라 로봇 외형과 수업 보조 서비스에 대한 선호도 차이를 알아봄으로써, 초등학교에서 유비퀴터스 로봇을 이용한 r-Learning에 있어서 일시적 신기효과가 아닌 지속적인 영향을 줄 수 있는 요인을 찾아보았다. 실험 결과, 지속적인 HRI 유지에 영향을 끼칠 수 있는 외형적 요인으로 로봇 얼굴과 로봇과 아동간 관계성을 지향하는 컨텐츠 개발이 필요함을 보였다.