• Journal of Digital Convergence
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• v.20 no.2
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• pp.511-523
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• 2022

This study was conducted using non-face-to-face care technology for the elderly with mild dementia and the physically weak living in the community, as various methods of care for the elderly have been raised due to the prolonged COVID-19. The purpose of this study is a similar experimental study before and after the inequality control group to compare cognitive function, daily living activities, and the degree of depression by applying an AI robot integrated management program using. The data was collected from June 4 to September 17, 2021, and the survey results of 17 people in the experimental group and 18 in the control group were analyzed using the SPSS 25.0 program. As a result of the study, the experimental group was significant in language function, activities of daily living, and depression. In particular, the results showed a decrease in moderate to severe depression and mild depression. Cognitive function was significant with long-term care grade and daily living activity with family living together. Therefore, if such non-face-to-face care technology is introduced to the elderly care field in the 'With Corona era', it is thought that it will contribute to cognitive function training and depression reduction of the elderly.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.70-75
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• 2016

Nowadays, there are many research for recognizing face of people using the machine vision. the machine vision is classification and analysis technology using machine that has sight such as human eyes. In this paper, we propose algorithm for classifying human face using this machine vision system. This algorithm consist of Convolutional Neural Network and cascade face detector. And using this algorithm, we classified the face of subjects. For training the face classification algorithm, 2,000, 3,000, and 4,000 images of each subject are used. Training iteration of Convolutional Neural Network had 10 and 20. Then we classified the images. In this paper, about 6,000 images was classified for effectiveness. And we implement the system that can classify the face of subjects in realtime using USB camera.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.507-511
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• 2006

Intelligent robot is defined as a system that it judges autonomously based on sensory organ of sight, hearing etc.. analogously with human. Human communicates using nonverbal means such as gesture in addition to language. If robot understands such nonverbal communication means, robot may become familiar with human . HCI (Human Computer Interaction) technologies are studied vigorously including face recognition and gesture recognition, but they are many problems that must be solved in real conditions. In this paper, we introduce the importance of contents and give application example of technology stressed on the recent research result about gesture recognition technology as one of most natural communication method with human.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.10a
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• pp.742-745
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• 2004

If a personal robot is popularized like a personal computer in the future, many kinds of robots will appear and the number of manufacturers will increase as a matter of course. In such circumstances, it can be inefficient, in case each manufacturer makes a whole platform individually. The solutions for this problem are to modularize a robot component (hardware and software) functionally and to standardize each module. Each module is developed and sold by each special maker and a consumer purchases desired modules and integrates them. The standardization of a module includes the unification of electrical and mechanical interface. In this paper, the standard interfaces of modules are proposed and CMR(Component Modularized Robot)-P2 made with the modules(brain, sensor, mobile, arm) is introduced. In order to simplify and to make the modules light, a frame is used for supporting a robot and communication/power lines. The name of a method and the way to use that are defined dependently on the standard interfaces in order to use a module in other modules. Each module consists of a distributed object and that can be implemented in the random language and platform. The sensor, mobile and arm modules are developed on Pentium or ARM CPU and embedded Linux OS using the C programming language. The brain module is developed on Pentium CPU and Windows OS using the C, C++ and RPL(Robot Programming Language). Also tasks like pass planning, localization, moving, object perception and face perception are developed. In our test, modules got into gear and CMR-P2 executed various scenarios like guidance, errand and guarding completely.

• The Journal of Korean Institute for Practical Engineering Education
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• v.1 no.1
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• pp.91-98
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• 2009

In approach of human-robot interaction, it is importance task in future robot industry to make to robot recognize, express, coping the emotions. The purpose of this study was to examination the effects unconscious positive and negative emotion of information processing of motor program. 13 participants(male=11, female=2) viewed smile-face picture and angry-face picture priming at 10ms level, and then performanced button press, button press and one tennis ball hitting, and button press and two tennis ball hitting task. The results appeared that positive emotion triggered more fast RT than negative emotion in planning complex motor program. Possible explanations for the performance differences depended on emotion are discussed and future research directions were provided.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.11
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• pp.1074-1081
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• 2007

This paper presents a method for real-time face detection and tracking which combined Adaboost and Camshift algorithm. Adaboost algorithm is a method which selects an important feature called weak classifier among many possible image features by tuning weight of each feature from learning candidates. Even though excellent performance extracting the object, computing time of the algorithm is very high with window size of multi-scale to search image region. So direct application of the method is not easy for real-time tasks such as multi-task OS, robot, and mobile environment. But CAMshift method is an improvement of Mean-shift algorithm for the video streaming environment and track the interesting object at high speed based on hue value of the target region. The detection efficiency of the method is not good for environment of dynamic illumination. We propose a combined method of Adaboost and CAMshift to improve the computing speed with good face detection performance. The method was proved for real image sequences including single and more faces.

• Journal of Information Technology Services
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• v.15 no.4
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• pp.1-24
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• 2016

With the innovation of information technology, non-face-to-face robo advisor with high accessibility and convenience is spreading. The current robot advisor recommends appropriate investment products after understanding the investment propensity based on the structured data entered directly or indirectly by individuals. However, it is an inconvenient and obtrusive way for financial consumers to inquire or input their own subjective propensity to invest. Hence, this study proposes a way to deduce the propensity to invest in unstructured data that customers voluntarily exposed during consultation or online. Since prediction performance based on unstructured document differs according to the characteristics of text, in this study, classification algorithm optimized for the characteristic of text left by financial consumers is selected by performing prediction performance evaluation of various learning discrimination algorithms and proposed an intelligent method that automatically recommends investment products. User tests were given to MBA students. After showing the recommended investment and list of investment products, satisfaction was asked. Financial consumers' satisfaction was measured by dividing them into investment propensity and recommendation goods. The results suggest that the users high satisfaction with investment products recommended by the method proposed in this paper. The results showed that it can be applies to non-face-to-face robo advisor.

• Journal of The Korean Association of Information Education
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• v.15 no.3
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• pp.483-492
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• 2011

'Learning with a robot' is now considered as one of the best candidates for STEAM education, which is recently growing its importance. Most of the 'learning with a robot' programs in elementary schools serve as afterschool classes. The students participating in the afterschool classes are mostly boys who are interested in science and robots. This paper mainly concerns that a robot can be helpful for improving students' interest in STEAM education. We divided the robot utilizable aspects into 5 areas with educational points of view; abstract concept understanding type, structure-oriented type, athletics-oriented type, intelligence-oriented type and value-orientated type. We extracted all robot utilizable subjects and units from elementary school curriculum, and developed lesson plans which can be applicable to regular classes. And we also verified them by applying into an elementary school for 5 months. As the result of the analysis, we can conclude that 'learning with a robot' can encourage students' interest in STEAM, and it is more effective for girls than boys. Finally, we discuss problems that teachers may face in using a robot for regular classes, and make suggestions about the use of a robot for STEAM education.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.75-87
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• 1998

KARES (KAIST Rehabilitation Engineering System) is the rehabilitation robot system in the type of the 6 degrees of freedom robot arm mounted on the wheelchair, in order to assist the independent livelihood of the disabled and the elderly. The interface device for programming and controlling of the robot arm is essential in the rehabilitation robotic system. Specially, in the case of the manual operation of the robot arm, the user has the burden of cognition and the difficulty for the operation of the robot arm. As a remedy, color vision system for the autonomous performance of jobs is proposed, and four basic desired jobs are specified. By mounting the camera in eye-in-hand type, color vision system for KARES is set up. The desired jobs for picking up the target and moving it to the user's face for drinking are successfully performed in real-time at the indoor environment.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.147-149
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• 2004

There are no authentic solutions in a face region extraction problem though it is an important part of pattern recognition and has diverse application fields. It is not easy to develop the facial region extraction algorithm because the facial image is very sensitive according to age, sex, and illumination. In this paper, to solve these difficulties, a fuzzy color filer based on the facial region extraction algorithm is proposed. The fuzzy color filter makes the robust facial region extraction enable by modeling the skin color. Especially, it is robust in facial region extraction with various illuminations. In addition, to identify the fuzzy color filter, a linear matrix inequality(LMI) optimization method is used. Finally, the simulation result is given to confirm the superiority of the proposed algorithm.