• Journal of Korean Library and Information Science Society
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• v.51 no.4
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• pp.211-230
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• 2020

The purpose of this study is to contribute to improving the efficiency of managing the database of the reports arising from the results of National R&D projects. To that end, the reports submitted by 49 agencies under the Ministry of Science and ICT were collected, and samples were selected for each institution. The samples and form of the final report and summary of the Enforcement Rule of the Framework Act on Science and Technology were compared, and the components and items to be entered were established. The final report's unique items were derived from the analysis of the state of connection with the National R&D information standard. The items to be entered are classified into major and optional according to their importance, and the location of the entry to be entered is suggested. If standardization of the elements and items is advanced as planned, it is expected to automate metadata extraction and improve the quality of report metadata when building a database.

• The KIPS Transactions:PartD
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• v.14D no.6
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• pp.573-584
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• 2007

As multimedia information recently increases fast, various types of retrieval of multimedia data are becoming issues of great importance. For the efficient multimedia data processing, semantics based retrieval techniques are required that can extract the meaning contents of multimedia data. Existing retrieval methods of multimedia data are annotation-based retrieval, feature-based retrieval and annotation and feature integration based retrieval. These systems take annotator a lot of efforts and time and we should perform complicated calculation for feature extraction. In addition. created data have shortcomings that we should go through static search that do not change. Also, user-friendly and semantic searching techniques are not supported. This paper proposes to develop S-MARS(Semantic Metadata-based Multimedia Annotation and Retrieval System) which can represent and extract multimedia data efficiently using MPEG-7. The system provides a graphical user interface for annotating, searching, and browsing multimedia data. It is implemented on the basis of the semantic metadata model to represent multimedia information. The semantic metadata about multimedia data is organized on the basis of multimedia description schema using XML schema that basically comply with the MPEG-7 standard. In conclusion. the proposed scheme can be easily implemented on any multimedia platforms supporting XML technology. It can be utilized to enable efficient semantic metadata sharing between systems, and it will contribute to improving the retrieval correctness and the user's satisfaction on embedding based multimedia retrieval algorithm method.

• Journal of the Korean Society for information Management
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• v.24 no.4
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• pp.53-72
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• 2007

This study is designed to assess whether storyboard surrogates are useful enough to be utilized for indexing sources as well as for metadata elements using 12 sample videos and 14 participants. Study shows that first, the match rates of index terms and summaries are significantly different according to video types, which means storyboard surrogates are especially useful for the type of videos of conveying their meanings mainly through images. Second, participants could assign subject keywords and summaries to digital video, sacrificing a little loss of full video clips' match rates. Moreover, the match rate of index terms (0.45) is higher than that of summaries (0.40). This means storyboard surrogates could be more useful for indexing videos rather than summarizing them. The study suggests that 1)storyboard surrogates can be used as sources for indexing and abstracting digital videos; 2) using storyboard surrogates along with other metadata elements (e.g., text-based abstracts) can be more useful for users' relevance judgement; and 3)storyboard surrogates can be utilized as match sources of image-based queries. Finally, in order to improve storyboard surrogates quality, this study proposes future studies: constructing key frame extraction algorithms and designing key frame arrangement models.

• Journal of Korea Multimedia Society
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• v.12 no.8
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• pp.1043-1054
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• 2009

As the semantic web receives higher concern with an intensified necessity in these days, the research on the ontology as its core technology has been carried out in various fields. The ontology has been adopted as an alternative to work out lots of problematic issues resulted from the insufficient vocabulary selection rules in folksonomy, widely accepted under Web 2.0. Therefore the importance of research to complementarily consolidate the two disciplines, the folksonomy and the ontology, has been increased. Based on this idea this research proposes a system, which pulls out, using open services, the location information tags from folksonomy-based metadata, ultimately extracts, following location information analyses, spatial relationships among tags, and in turn automatically constructs self-correcting location information domain ontology. The system devised in this study will associate data derived from easily accessible folksonomy with meaningful and technological information from ontology.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2004.11a
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• pp.237-240
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• 2004

This paper describes a character retrieval system for TV programs and a set of novel algorithms for detecting and recognizing faces for the system. Our character retrieval system consists of two main components: Face Register and Face Recognizer. The Face Register detects faces in video frames and then guides users to register the detected faces of interest into the database. The Face Recognizer displays the appearance interval of each character on the timeline interface and the list of scenes with the names of characters that appear on each scene. These two components also provide a function to modify incorrect results. which is helpful to provide accurate character retrieval services. In the proposed face detection and recognition algorithms. we reduce the computation time without sacrificing the recognition accuracy by using the DCT/LDA method for face feature extraction. We also develop the character retrieval system in the form of plug-in. By plugging in our system to a cataloguing system. the metadata about the characters in a video can be automatically generated. Through this system, we can easily realize sophisticated on-demand video services which provide the search of scenes of a specific TV star.

• ETRI Journal
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• v.44 no.1
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• pp.38-50
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• 2022

This paper presents a study on the use of encoder-derived features in decoder-side depth estimation. The scheme of multiview video encoding does not require the transmission of depth maps (which carry the geometry of a three-dimensional scene) as only a set of input views and their parameters are compressed and packed into the bitstream, with a set of features that could make it easier to estimate geometry in the decoder. The paper proposes novel recursive block splitting for the feature extraction process and evaluates different scenarios of feature-driven decoder-side depth estimation, performed by assessing their influence on the bitrate of metadata, quality of the reconstructed video, and time of depth estimation. As efficient encoding of multiview sequences became one of the main scopes of the video encoding community, the experimental results are based on the "geometry absent" profile from the incoming MPEG Immersive video standard. The results show that the quality of synthesized views using the proposed recursive block splitting outperforms that of the state-of-the-art approach.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.147-149
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• 2021

Recently, the rapid growth of the media market and the expectations of users have been increasing. In this research, tags are extracted through media-derived audio and classified into specific categories using artificial intelligence. This category is a type of emotion including joy, anger, sadness, love, hatred, desire, etc. We use JupyterNotebook to conduct the corresponding study, analyze voice data using the LiBROSA library within JupyterNotebook, and use Neural Network using keras and layer models.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.54 no.5
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• pp.315-323
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• 2005

The recent development of embodiment technology of the medical images makes most medical institutions introduce PACS in haste. However, while many older HIS and PACS systems are not yet capable of some of the integration, several new systems are moving rapidly in that direction. Typical PACS system architecture begins with the HIS since this is where the correct patient demographic information and in many cases the orders originate. So, PACS developed convenience of users and to satisfy user's demand because of financial limitations and administrator-oriented considerations in the process of development. Therefore, we have developed a CDA (Clinical Document Architecture) based PACS with HIS, by which we can search and refer to the patient's medical images and information with few restrictions of time and space for diagnosis and treatment. Target model of this research limited to 135 of hospital have 200 beds. We'll make more effort to develop the application which insures the better quality and information of medical images. Medical Image History manages the patient's image files and various medical informations like film chart in connection with time. This trial will contribute to the reduction of the financial loss caused by unnecessary devices and improve the quality in the medical services. The demand on the development of the program which refers to the medical data quickly and keeps them stable will be continued by the medical institute. This will satisfy the client's demand and improve the service to the patients in that the program will be modified from the standpoint of the users.

• Journal of the Korea Society of Computer and Information
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• v.14 no.11
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• pp.21-30
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• 2009

Semantic web uses ontology languages such as RDF, RDFS, and OWL to define the metadata on the web. There have been many researching efforts in the semantic web technologies based on an agent for extracting triple and relation about concept of ontology. But the extraction of relation and triple about the concept of ontology based on an agent ends up writing a limited query statement as characteristics of an agent. As for this, there is the less of flexibility when extracting triple and relation about the other concept of ontology. We are need a query tool for flexible information retrieval of ontology that is can access the standard ontology and can be used standard query language. In this paper, we propose a SPARQL query tool that is can access the OWL ontology via HTTP protocol and it can be used to make a query. Query result can be output to the soap message. These operations can be support the web service.

• Phonetics and Speech Sciences
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• v.15 no.2
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• pp.43-51
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• 2023

In this paper, we propose an approach for dialect classification based on the speed and pause of speech utterances as well as the age and gender of the speakers. Dialect classification is one of the important techniques for speech analysis. For example, an accurate dialect classification model can potentially improve the performance of speaker or speech recognition. According to previous studies, research based on deep learning using Mel-Frequency Cepstral Coefficients (MFCC) features has been the dominant approach. We focus on the acoustic differences between regions and conduct dialect classification based on the extracted features derived from the differences. In this paper, we propose an approach of extracting underexplored additional features, namely the speed and the pauses of speech utterances along with the metadata including the age and the gender of the speakers. Experimental results show that our proposed approach results in higher accuracy, especially with the speech rate feature, compared to the method only using the MFCC features. The accuracy improved from 91.02% to 97.02% compared to the previous method that only used MFCC features, by incorporating all the proposed features in this paper.