• Proceedings of the IEEK Conference
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• 2002.06e
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• pp.193-196
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• 2002

In this paper, we presents the remote inspection activity with a mobile robot at the calandria face areas of the PHWR (pressurized heavy water reactor) nuclear power plants during full power plant operation.. The tele-operated mobile robot has been developed for this task. A 4 wheeled mechanism with the dual reconfigurable crawler arm has been adopted for the ease access to the high radiation area of calandria face. A specially designed extendable long reach mast attached on the mobile platform and the thermal image monitoring system enable human eyes to look into the calandria face. Application of robot will keep human workers from high radiation exposure and enhance the reliability of nuclear power plants.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.155-164
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• 2004

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user and is able to doface recognition, which is vital for many surveillance-based systems. The advantage of face recognition compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to the decreasing in dimension from image acquisition step and various changes associated with face pose and background. There are many factors that deteriorate performance of face recognition such as thedistance from camera to the face, changes in lighting, pose change, and change of facial expression. In this paper, we implement a new sliding active camera system to prevent various pose variation that influence face recognition performance andacquired frontal face images using PCA and HMM method to improve the face recognition. This proposed face recognition algorithm can be used for intelligent surveillance system and mobile robot system.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.935-936
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• 2006

In this paper, we have applied a real-time face processor includes detection, recognition, and learning to a intelligent store management service robot. We use the Haar classifier and adaboost learning algorithm for face detection. For face recognition and learning, a PCA algorithm and a SVDD algorithm is used. We have developed a store management service robot and applied these algorithms to verify the performance.

• ETRI Journal
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• v.33 no.2
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• pp.251-258
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• 2011

Applying face alignment after face detection exerts a heavy influence on face recognition. Many researchers have recently investigated face alignment using databases collected from images taken at close distances and with low magnification. However, in the cases of home-service robots, captured images generally are of low resolution and low quality. Therefore, previous face alignment research, such as eye detection, is not appropriate for robot environments. The main purpose of this paper is to provide a new and effective approach in the alignment of small and blurred faces. We propose a face alignment method using the confidence value of Real-AdaBoost with a modified census transform feature. We also evaluate the face recognition system to compare the proposed face alignment module with those of other systems. Experimental results show that the proposed method has a high recognition rate, higher than face alignment methods using a manually-marked eye position.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.605-606
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• 2009

• Journal of Convergence for Information Technology
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• v.10 no.4
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• pp.1-10
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• 2020

The performance of the personalized product recommendation system for offline shopping malls is poor compared with the one using online environment information since it is difficult to obtain visitors' characteristic information. In this paper, a mobile robot platform is suggested capable of recommending personalized advertisement using customers' sex and age information provided by Face API of MS Azure Cloud service. The performance of the developed robot is verified through locomotion experiments, and the performance of API used for our robot is tested using sampled images from open Asian FAce Dataset (AFAD). The developed robot could be effective in marketing by providing personalized advertisements at offline shopping malls.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.10a
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• pp.213-214
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• 2012

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.217-218
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• 2007

Face recognition, recognizing the human faces, is one of the most important techniques for making intelligent robot that provide commendable services to human. In this paper, we make a comparative study of Original PCA, 2DPCA, 2DPCA based algorithms and LDA in robot environment. Database is obtained through the robot's camera in a laboratory what is made like home environment for experiment.. We consider distance state what can be generated in home environment for database.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1485-1490
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• 2004

Recently, we have remarkable developments in intelligent robot systems. The remarkable features of intelligent robot are that it can track user, does face recognition and vital for many surveillance based systems. Advantage of face recognition when compared with other biometrics recognition is that coerciveness and contact that usually exist when we acquire characteristics do not exist in face recognition. However, the accuracy of face recognition is lower than other biometric recognition due to decrease in dimension from of image acquisition step and various changes associated with face pose and background. Factors that deteriorate performance of face recognition are many such as distance from camera to face, lighting change, pose change, and change of facial expression. In this paper, we implement a new 3D active camera system to prevent various pose variation that influence face recognition performance and propose face recognition algorithm for intelligent surveillance system and mobile robot system.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.371-376
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• 2007

This paper presents an emotion recognition and its expression system of an intelligent robot like a home robot or a service robot. Emotion recognition method in the robot is used by a facial image. We use a motion and a position of many facial features. apply a tracking algorithm to recognize a moving user in the mobile robot and eliminate a skin color of a hand and a background without a facial region by using the facial region detecting algorithm in objecting user image. After normalizer operations are the image enlarge or reduction by distance of the detecting facial region and the image revolution transformation by an angel of a face, the mobile robot can object the facial image of a fixing size. And materialize a multi feature selection algorithm to enable robot to recognize an emotion of user. In this paper, used a multi layer perceptron of Artificial Neural Network(ANN) as a pattern recognition art, and a Back Propagation(BP) algorithm as a learning algorithm. Emotion of user that robot recognized is expressed as a graphic LCD. At this time, change two coordinates as the number of times of emotion expressed in ANN, and change a parameter of facial elements(eyes, eyebrows, mouth) as the change of two coordinates. By materializing the system, expressed the complex emotion of human as the avatar of LCD.