• Archives of design research
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• v.19 no.1 s.63
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• pp.79-88
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• 2006

A human face figure is a visual symbol of identity. Each different face per person is a critical information differentiating each person from others and it directly relates to individual identity. When we look back human history, historical change of recognition for a face led to the change of expression and communication media and it in turn caused many changes in expressing a face. However, there has not been no time period when people pay attention to a face more than this time. Technically, the advent of computer graphics opened new turning point in expressing human face figure. Especially, a visual image which can be produced, saved, and transferred in digital has no limitation in time and space, and its importance in communication is getting higher and higher. Among those visual image information, a face image in digital is getting more applications. Therefore, 3d (3-dimensional) expression of a face using computer graphics can be easily produced without any professional techniques, just like assembling puzzle parts composed of the shape of each part ands texture map, etc. This study presents a method with which a general visual designer can effectively express 3d type face by studying each producing step of 3d face expression and by visualizing case study based on the above-mentioned study result.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.243-262
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• 2022

In this study, eye tracking was used for the appearance of the robot during the social robot design study. During the research, each part of the social robot was designated as AOI (Areas of Interests), and the user's attitude was measured through a design evaluation questionnaire to construct a design research model of the social robot. The data used in this study are Fixation, First Visit, Total Viewed, and Revisits as eye tracking indicators, and AOI (Areas of Interests) was designed with the face, eyes, lips, and body of the social robot. And as design evaluation questionnaire questions, consumer beliefs such as Face-highlighted, Human-like, and Expressive of social robots were collected and as a dependent variable was attitude toward robots. Through this, we tried to discover the mechanism that specifically forms the user's attitude toward the robot, and to discover specific insights that can be referenced when designing the robot.

• Journal of Korea Multimedia Society
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• v.23 no.12
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• pp.1586-1593
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• 2020

This study was conducted on the face ratio of mammals. It can also be applied to character automation by checking factors about the difference between animal and human face shapes. This paper used the face and face area data generated for Deep Learning learning. In detail, the proportion factors of the area comprising the faces of 20 species of animals and humans were defined and the average ratio was calculated. Next, the proportion of each animal was analyzed using the Principal Component Analysis (PCA). Through this, we would like to propose the golden ratio of mammals.

• 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.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1252-1255
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• 2002

In this paper, face recognition algorithm, by using skin color information of HSI color coordinate collected from face images, elliptical mask, fratures of face including eyes, nose and mouth, and geometrical feature vectors of face and facial angles, is proposed. The proposed algorithm improved face region extraction efficacy by using HSI information relatively similar to human's visual system along with color tone information about skin colors of face, elliptical mask and intensity information. Moreover, it improved face recognition efficacy with using feature information of eyes, nose and mouth, and Θ1(ACRED), Θ2(AMRED) and Θ 3(ANRED), which are geometrical face angles of face. In the proposed algorithm, it enables exact face reading by using color tone information, elliptical mask, brightness information and structural characteristic angle together, not like using only brightness information in existing algorithm. Moreover, it uses structural related value of characteristics and certain vectors together for the recognition method.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.615-617
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• 1998

This paper proposes a new segmentation method of human races from grey scale images with clutter using a racial template and elliptical structure of the human head. Face detection technique can be applied in many areas of image processing such as face recognition, composition and computer graphics. Until now, many researches about face detection have been conducted, and applications in more complicated conditions are increasing. The general case is more in a complicated background than in a simple one, and a image with not only one face. Research and development of face detection in such a general case are growing rapidly, and the necessity for that is increasing continuously. Sirohey proposed a face detection method using linearized elliptical equation. The method designed in this paper is improved to be applicable even in the more general cases like where the face is much smaller than the image size and with many faces in one image using template matching and elliptic fitting technique.

• Proceedings of the IEEK Conference
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• 2001.06c
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• pp.81-84
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• 2001

The retrieval techniques of multimedia contents have been developed along with MPEG-7. But as human being distinguishes objects with the eyesight, researches for high retrieval efficiency applied a high level computer vision technology are difficult because of the increase of processing time caused by complexity of algorithm, and the difficulty of an implementation. In this paper, for an effective news retrieval using the human face information, we suggest a method which extracts face information like as location, size and number of the face in the news video, and then we prove the validity of method by experiment.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.11
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• pp.991-999
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• 2004

Face robots capable of expressing their emotional status, can be adopted as an efficient tool for friendly communication between the human and the machine. In this paper, we present a face robot actuated with artificial muscle based on dielectric elastomer. By exploiting the properties of polymers, it is possible to actuate the covering skin, eyes as well as provide human-like expressivity without employing complicated mechanisms. The robot is driven by seven types of actuator modules such as eye, eyebrow, eyelid, brow, cheek, jaw and neck module corresponding to movements of facial muscles. Although they are only part of the whole set of facial motions, our approach is sufficient to generate six fundamental facial expressions such as surprise, fear, anger, disgust, sadness, and happiness. Each module communicates with the others via CAN communication protocol fur the desired emotional expressions, the facial motions are generated by combining the motions of each actuator module. A prototype of the robot has been developed and several experiments have been conducted to validate its feasibility.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.05a
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• pp.656-659
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• 2001

Human have a notable ability to recognize faces, which is one of the most common visual feature in our environment. In regarding face pattern, just like other natural object, a geometrical interpretation of face is difficult to achieve. In this paper, we present wavelet based approach to extract the face features. Proposed approach is similar to the feature based scheme, where the feature is derived from the intensity data without detecting any knowledge of the significant feature. Topological graphs are involved to represent some relations between facial features. In our experiments, proposed approach is less sensitive to the intensity variation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.2
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• pp.349-355
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• 2001

Human have a notable ability to recognize faces, which is one of the most common visual feature in our environment. In regarding face pattern, just like other natural object, a geometrical interpretation of face is difficult to achieve. In this paper, we present wavelet based approach to extract the face features. Proposed approach is similar to the feature based scheme, where the feature is derived from the intensity data without detecting any knowledge of the significant feature. Topological graphs are involved to represent some relations between facial features. In our experiments, proposed approach is less sensitive to the intensity variation.