• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.22 no.3
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• pp.303-309
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• 2004

In this paper, an adaptive Bayesian approach to image segmentation was developed for boundary detection. Both image intensities and texture information were used for obtaining better quality of the image segmentation by using the C programming language. Fuzzy c-mean clustering was applied fer the conditional probability density function, and Gibbs random field model was used for the prior probability density function. To simply test the algorithm, a synthetic image (256$\times$256) with a set of low gray values (50, 100, 150 and 200) was created and normalized between 0 and 1 n double precision. Results have been presented that demonstrate the effectiveness of the algorithm in segmenting the synthetic image, resulting in more than 99% accuracy when noise characteristics are correctly modeled. The algorithm was applied to the Antarctic mosaic that was generated using 1963 Declassified Intelligence Satellite Photographs. The accuracy of the resulting vector map was estimated about 300-m.

• Journal of Korea Spatial Information System Society
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• v.11 no.1
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• pp.35-42
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• 2009

This paper proposes a new GeoPhoto contents markup language that can create u-GIS contents by using the spatial photos. GeoPhoto contents markup language has designed the GeoPhoto contents model and markup language for contents that can be used the spatial photos information. GeoPhoto con tents markup language is represented by the convergence of GIS information, location information, photos information respectively. GeoPhoto contents markup language to provide a variety of pictures related to the content model consists of GeoPhoto contents model and operations between the GeoPhoto contents. GeoPh oto contents model supports GeoPhoto model, CubicPhoto model, Photo model and SequenceGeoPhoto mod el. In addition, this paper propose the Annotation operation, Enlargement operation and Overlay operation for represent the GeoPhoto contents. GeoPhoto Contents Markup Language has the advantage of supportin g user custom contents model of u-GIS.

• Cartoon and Animation Studies
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• s.9
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• pp.184-198
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• 2005

Characters are composed of universal value system that can be applied to the oriental and western world, while there are based on the differences in general and cultural values distinguished by the said two worlds. In modern society expressed as the age of moving image, the products concerning the characters have played a role as a forerunner of the spread of culture in the formation of new markets, regardless of considering the relationship between animation industry in Korea and the counterparts in the USA and Japan. Furthermore, as a successful role model, eastern and western character industries have penetrated deeply into our daily lives, in terms of our cultural values. Based on the assumption that characters reflect the cultural values, This study investigates the meanings of bodily & linguistic expressions appeared in animation characters and reviews the method of enhancing their values and effectiveness as cultural assets.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.375-381
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• 2016

Recently, a foreground-background segmentation using codebook model has been researched actively. The codebook is created one for each pixel in the image. The codewords are vector-quantized representative values of same positional training samples from the input image sequences. The training is necessary for a long time in the most of codebook-based algorithms. In this paper, the initial codebook model is generated simply using median operation with several image frames. The initial codebook is updated to adapt the dynamic changes of backgrounds based on the frequencies of codewords that matched to input pixel during the detection process. We implemented the proposed algorithm in the environment of visual c++ with opencv 3.0, and tested to some of the public video sequences from PETS2009. The test sequences contain the various scenarios including quasi-periodic motion images, loitering objects in the local area for a short time, etc. The experimental results show that the proposed algorithm has good performance compared to the GMM algorithm and standard codebook algorithm.

• The Journal of the Korea Contents Association
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• v.14 no.5
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• pp.512-523
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• 2014

The purpose of this study is to provide useful information for improving interaction between teacher and student by analysing gifted class in mathematics with the Flanders Category System. Research questions are as follow. In gifted class in mathematics, How is the result of analysis regarding interactions between the teacher and students, according to 1) Flanders' Coding system? 2) Flanders' language pattern? 3) Flanders' Index system? For this, 3 gifted classes in mathematics were recorded by video camera and analyzed by Advanced Flanders(AF) analysis program version 3.54. Results are as follow. 1) Code Category Analysis mostly consists of lecture, voluntary speaking and chaos, silence work. 2) Most class patterns are not in accordance with effective class pattern models. So teacher needs to accept student's opinion actively and give appropriate feedback. 3) In Indices Results, revised I/d ratio, teacher's question ratio, student's speaking ratio, Student question and wide answer ratio are higher than analysis standard, indirect ratio is lower than analysis standard.

• Proceedings of the Korean Information Science Society Conference
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• 2005.11b
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• pp.736-738
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• 2005

최근 PDA나 PMP와 같은 개인용 모바일 기기의 인터페이스 개발로써 잡음환경에 강인한 음성인식 기술들이 연구되고 있으며 이러한 방법으로 오류패턴, 순차패턴, 의미정보, 문맥정보와 같이 인식기에 독립적인 정보를 이용하거나 영상 정보와 같이 언어와 성격이 다른 이질적인 정보를 이용하여 후처리를 하는 연구들이 진행되어 왔다. 그러나 인식기와 독립적인 정보로 후처리를 하는 방법들의 인식률은 인식기의 사전 인식률이 주변 잡음에 의해 떨어질 경우 후처리 인식률도 같이 떨어지는 현상이 벌어진다. 따라서 본 논문에서는 주변 잡음으로 인한 인식기의 사전 인식률에 저하를 줄이는 방법으로 사용자 적응형 후처리를 제안한다. 사용자 적응형 후처리에 사용되는 데이터는 사용자의 발화에 대한 인식기의 출력 값들이며, 출력 값들은 화자독립모델에 의해 계산되는 각 단어들의 유사도 들이다. 따라서 화자독립모델의 결과를 사용자 적응형 후처리에 적용한 결과 인식기의 오류를 $58.7\%$ 줄일 수 있었다.

• Journal of Advanced Navigation Technology
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• v.25 no.6
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• pp.557-561
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• 2021

A meatadata has become an essential element in order to recommend video content to users. However, it is passively generated by video content providers. In the paper, a method for automatically generating metadata was studied in the existing manual metadata input method. In addition to the method of extracting emotion tags in the previous study, a study was conducted on a method for automatically generating metadata for genre and country of production through movie audio. The genre was extracted from the audio spectrogram using the ResNet34 artificial neural network model, a transfer learning model, and the language of the speaker in the movie was detected through speech recognition. Through this, it was possible to confirm the possibility of automatically generating metadata through artificial intelligence.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.59-68
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• 1999

Recently, research and developmental direction of communication system is concurrent adopting voice data and face image in speaking to provide more higher recognition rate then in the case of only voice data. Therefore, we present a method of lipreading in speech image sequence by using the 3-D facial shape model. The method use a feature information of the face image such as the opening-level of lip, the movement of jaw, and the projection height of lip. At first, we adjust the 3-D face model to speeching face image sequence. Then, to get a feature information we compute variance quantity from adjusted 3-D shape model of image sequence and use the variance quality of the adjusted 3-D model as recognition parameters. We use the intensity inclination values which obtaining from the variance in 3-D feature points as the separation of recognition units from the sequential image. After then, we use discrete HMM algorithm at recognition process, depending on multiple observation sequence which considers the variance of 3-D feature point fully. As a result of recognition experiment with the 8 Korean vowels and 2 Korean consonants, we have about 80% of recognition rate for the plosives and vowels. We propose that usability with visual distinguishing factor that using feature vector because as a result of recognition experiment for recognition parameter with the 10 korean vowels, obtaining high recognition rate.

• Journal of Creative Information Culture
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• v.4 no.2
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• pp.95-101
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• 2018

As a result of introducing robot assisted learning which utilizes social robots or telepresence robots in language learning or special education, research on technology acceptance model for robot-assisted learning is also being conducted. The unified theory of acceptance and use of technology (UTAUT) model of intelligent robot has been studied, but of tele-operated robot is insufficient. The purpose of this paper is to estimate the UTAUT model by pre-service teachers who experienced telepresence robot-assisted learning that can be done in future school. It is found that the estimated UTAUT model consists of more concise factors than social robots, and the importance of perceived enjoyment is higher. In other words, the pre-service teachers showed significant acceptance of tele-operated robots with enhanced enjoyment composed of its mobility, communication, and touchable appearance of the face and body.

• The Journal of Society for e-Business Studies
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• v.24 no.3
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• pp.87-98
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• 2019

As artificial intelligence is actively studied, it is being applied to various fields such as image, video and natural language processing. The natural language processing, in particular, is being studied to enable computers to understand the languages spoken and spoken by people and is considered one of the most important areas in artificial intelligence technology. In natural language processing, it is a complex, but important to make computers learn to understand a person's common sense and generate results based on the person's common sense. Knowledge graphs, which are linked using the relationship of words, have the advantage of being able to learn common sense easily from computers. However, the existing knowledge graphs are organized only by focusing on specific languages and fields and have limitations that cannot respond to neologisms. In this paper, we propose an intelligent chatbotsystem that collects and analyzed data in real time to build an automatically scalable knowledge graph and utilizes it as the base data. In particular, the fine-tuned BERT-based for relation extraction is to be applied to auto-growing graph to improve performance. And, we have developed a chatbot that can learn human common sense using auto-growing knowledge graph, it verifies the availability and performance of the knowledge graph.