• Journal of Korea Multimedia Society
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• v.1 no.1
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• pp.1-17
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• 1998

Video information is an important component of multimedia systems such as Digital Library, World-Wide Web (WWW), and Video-On-Demand (VOD) service system. Video information has hierarchical document structure inherently, so it is named "structure video document" in this paper. This paper proposes a data model, a query language, and an indexing scheme for structured video documents in order to store, retrieve, and share video documents efficiently. In representing structured video documents, the object-oriented data modeling technique is used since the hierarchical structure information can be modeled as complex objects. We also define object types for the structure information. Our query language supports not only content-based retrieval, which means the queries based on the structure of video documents, and spatial/temporal relation for video documents. In order to perform structure queries efficiently, as well as to reduce the storage overhead of indices, an optimized inverted index structure is proposed.

• The Journal of the Acoustical Society of Korea
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• v.20 no.2
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• pp.10-15
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• 2001

In this paper, we describe the comparison between the combination of features using a speech and music discrimination, which is classifying between speech and music on audio signals. Audio signals are classified into 3classes (speech, music, speech and music) and 2classes (speech, music). Experiments carried out on three types of feature, Mel-cepstrum, energy, zero-crossings, and try to find a best combination between features to speech and music discrimination. We using a Gaussian Mixture Model (GMM) for discrimination algorithm and combine different features into a single vector prior to modeling the data with a GMM. In 3classes, the best result is achieved using Mel-cepstrum, energy and zero-crossings in a single feature vector (speech: 95.1％, music: 61.9％, speech & music: 55.5％). In 2classes, the best result is achieved using Mel-cepstrum, energy and Mel-cepstrum, energy, zero-crossings in a single feature vector (speech: 98.9％, music: 100％).

• Journal of KIISE:Databases
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• v.29 no.5
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• pp.381-392
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• 2002

This paper deals with the problem of shape-based retrieval in time-series databases. The shape-based retrieval is defined as the operation that searches for the (sub)sequences whose shapes are similar to that of a given query sequence regardless of their actual element values. In this paper, we propose an effective and efficient approach for shape-based retrieval of subsequences. We first introduce a new similarity model for shape-based retrieval that supports various combinations of transformations such as shifting, scaling, moving average, and time warping. For efficient processing of the shape-based retrieval based on the similarity model, we also propose the indexing and query processing methods. To verify the superiority of our approach, we perform extensive experiments with the real-world S&P 500 stock data. The results reveal that our approach successfully finds all the subsequences that have the shapes similar to that of the query sequence, and also achieves significant speedup up to around 66 times compared with the sequential scan method.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.3
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• pp.17-30
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• 2004

This study aimed to develop an agricultural drought assessment methodology for irrigated paddy field districts from a single reservoir. Agricultural drought was defined as the reservoir storage shortage state that cannot satisfy water requirement from the paddy fields. The suggested model, SRADEMP (a Single Reservoir Agricultural Drought Evaluation Model for Paddy), was composed of 4 submodels: PWBM (Paddy Water Balance Model), RWBM (Reservoir Water Balance Model), FA (Frequency and probability Analysis model), and DCI (Drought Classification and Indexing model). Two indices, PDF (Paddy Drought Frequency) and PDI (Paddy Drought Index) were also introduced to classify agricultural drought severity Both values were divided into 4 steps, i.e. normal, moderate drought, severe drought, and extreme drought. Each step of PDI was ranged from +4.2 to -1.39, from -1.39 to -3.33, from -3.33 to -4.0 and less than -4.0, respectively. SRADEMP was applied to Jangheung reservoir irrigation district, and the results showed good relationships between simulated results and the observed data including historical drought records showing that SRADEMP explains better the drought conditions in irrigated paddy districts than PDSI.

• Journal of Information Processing Systems
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• v.13 no.4
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• pp.951-969
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• 2017

In this paper, we newly propose a traffic information service model that collects traffic information sensed by an individual vehicle in real time by using a smart device, and which enables drivers to share traffic information on all roads in real time using an application installed on a smart device. In particular, when the driver requests traffic information for a specific area, the proposed driver-personalized service model provides him/her with traffic information on the driving directions in advance by predicting the driving directions of the vehicle based on the learning of the driving records of each driver. To do this, we propose a traffic information management model to process and manage in real time a large amount of online-generated traffic information and traffic information requests generated by each vehicle. We also propose a road node-based indexing technique to efficiently store and manage location-based traffic information provided by each vehicle. Finally, we propose a driving learning and prediction model based on the hidden Markov model to predict the driving directions of each driver based on the driver's driving records. We analyze the traffic information processing performance of the proposed model and the accuracy of the driving prediction model using traffic information collected from actual driving vehicles for the entire area of Seoul, as well as driving records and experimental data.

• Journal of Korea Multimedia Society
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• v.7 no.11
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• pp.1540-1549
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• 2004

In this paper, we propose an algorithm to detect semantic events in golf video using Hidden Markov Model. The purpose of this paper is to identify and classify the golf events to facilitate highlight-based video indexing and summarization. In this paper we first define 4 semantic events, and then design HMM model with states made up of each event. We also use 10 multiple visual features based on MPEG-7 visual descriptors to acquire parameters of HMM for each event. Experimental results showed that the proposed algorithm provided reasonable detection performance for identifying a variety of golf events.

• The Transactions of the Korea Information Processing Society
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• v.6 no.5
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• pp.1153-1165
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• 1999

In various fields of information technology, it is growing up the needs about dynamic content management systems to store and manage SGML(Standard Generalized Markup language) documents in a database system. In this paper, we consider the issue of storing SGML documents that having complex hierarchical structure into a database system, and then propose a data model based on ODMG(Object Database Management Group) object model in order to store SGML documents without loss of information. Because the proposed data model reflects physical element structure and logical entity structure of SGML documents, it is able to store the SGML document in a database system at the system at the element- level granularity without any information loss. And also the proposed data model can be adapted among ODMG-compliant object database management systems. Finally, we will discuss on the implementation details of SGML repository system supports the functionality of automatic database schema creation for any DTD(Document Type Definition0, the functionality of storing the SGML document, the functionality of dynamic document assembly from stored database objects to SGML document, and the functionality of indexing and searching for database objects.

• Journal of the HCI Society of Korea
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• v.9 no.2
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• pp.23-31
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• 2014

A variety of writing support systems focus on the information management or the feature analysis of the commercially successful narrative texts. In these approaches, the reader's role in the narrative creating process is overlooked. During a writing work, an author anticipates the reader's response or expectation to the narrative and he/she organizes the narrative either along or against the prediction about readers. Assessing and controlling the reader's comprehension in the development of events influences the aesthetic quality of the narrative. In this paper, we suggest a writing support system to visualize and adjust the characteristics of a narrative text related to the reader's comprehension, which is theoretically based on the narrative structure model and the event-indexing situation model. Under the development of the support system, we designed an interactive framework to create events as the basic units of story and arrange them onto both story- and discourse-time axes. Using this framework, we analyzed the organization of events about an actual film narrative. We also proposed both the continuity of the situational dimensions and the cognitive complexity as the characteristics to affect the reader's comprehension, hence we devised a method to visualize and evaluate them. This method was applied to the actual film narrative and the result was discussed in the aspect of the features of the narrative and wiring support strategies.

• The KIPS Transactions:PartB
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• v.12B no.1 s.97
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• pp.47-56
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• 2005

A moving object has a various features that its spatial location, shape, and size are changed as time goes. In addition, the moving object has both temporal feature and spatial feature. It is one of the highly interested feature information in video data. In this paper, we propose an efficient content-based multimedia information retrieval system, so tailed ECoMOT which enables user to retrieve video data by using a trajectory information of moving objects in video data. The ECoMOT includes several novel techniques to achieve content-based retrieval using moving objects' trajectories : (1) Muitiple trajectory modeling technique to model the multiple trajectories composed of several moving objects; (2) Multiple similar trajectory retrieval technique to retrieve more similar trajectories by measuring similarity between a given two trajectories composed of several moving objects; (3) Superimposed signature-based trajectory indexing technique to effectively search corresponding trajectories from a large trajectory databases; (4) convenient trajectory extraction, query generation, and retrieval interface based on graphic user interface

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.2 s.308
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• pp.1-11
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• 2006

In this paper, we propose the novel video retrieval algorithm using non-parametric based motion classification in the shot-based video indexing structure. The proposed system firstly gets the key frame and motion information from each shot segmented by scene change detection method, and then extracts visual features and non-parametric based motion information from them. Finally, we construct real-time retrieval system supporting similarity comparison of these spatio-temporal features. After the normalized motion vector fields is created from MPEG compressed stream, the extraction of non-parametric based motion feature is effectively achieved by discretizing each normalized motion vectors into various angle bins, and considering a mean, a variance, and a direction of these bins. We use the edge-based spatial descriptor to extract the visual feature in key frames. Experimental evidence shows that our algorithm outperforms other video retrieval methods for image indexing and retrieval. To index the feature vectors, we use R*-tree structures.