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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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The KIPS Transactions:PartB
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Korea Information Processing Society
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Volume & Issues
Volume 16B, Issue 6 - Dec 2009
Volume 16B, Issue 5 - Oct 2009
Volume 16B, Issue 4 - Aug 2009
Volume 16B, Issue 3 - Jun 2009
Volume 16B, Issue 2 - Apr 2009
Volume 16B, Issue 1 - Feb 2009
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AR-based Message Annotation System for Personalized Assistance
Vinh, Nguyen Van ; Jun, Hee-Sung ;
The KIPS Transactions:PartB, volume 16B, issue 6, 2009, Pages 435~442
DOI : 10.3745/KIPSTB.2009.16B.6.435
We propose an annotation system, which allows users moving on an environment to receive personalized messages that are generated by exploiting contextual information. In the system, the context is defined as an entity including user's identity, location and time. Identity of user is a key data to enable personal aspect of generated message. For sensing the context, the proposed system uses AR(augmented reality) technology. Markers are attached to real objects for tracking user's location. AR can provide an effective annotating method to enhance human's perception and interaction abilities. The received message can be a virtual post-it or three-dimensional virtual model of object overlaid onto the real-world view. Experimental results show that the proposed system works well in real-time with high performance and it can be used as a mobile service for personalized messaging.
Face Detection using Brightness Distribution in the Surrounding Area of Eye
Hwang, Dae-Dong ; Park, Joo-Chul ; Kim, Gye-Young ;
The KIPS Transactions:PartB, volume 16B, issue 6, 2009, Pages 443~450
DOI : 10.3745/KIPSTB.2009.16B.6.443
This paper develops a novel technique of face detection using brightness distribution in the surrounding area of eye. The proposed face detection consists of facial component candidate extraction, facial component candidate filtering through eye-lip combination, left/right eye classification using brightness distribution, face verification confirming edges in nose region. Because the proposed technique don't use any skin color, it can detect multiple faces in color images with complicated backgrounds and different illumination levels. The experimental results reveal that the proposed technique is better than the traditional techniques in terms of detection ratio.
A Semi-Automatic Building Modeling System Using a Single Satellite Image
Oh, Seon-Ho ; Jang, Kyung-Ho ; Jung, Soon-Ki ;
The KIPS Transactions:PartB, volume 16B, issue 6, 2009, Pages 451~462
DOI : 10.3745/KIPSTB.2009.16B.6.451
The spread of satellite image increases various services using it. Especially, 3D visualization services of the whole earth such as
or 3D GIS services for several cities provide realistic geometry information of buildings and terrain of wide areas. These service can be used in the various fields such as urban planning, improvement of roads, entertainment, military simulation and emergency response. The research about extracting the building and terrain information effectively from the high-resolution satellite image is required. In this paper, presents a system for effective extraction of the building model from a single high-resolution satellite image, after examine requirements for building model extraction. The proposed system utilizes geometric features of satellite image and the geometric relationship among the building, the shadow of the building, the positions of the sun and the satellite to minimize user interaction. Finally, after extracting the 3D building, the fact that effective extraction of the model from single high-resolution satellite will be show.
Fire-Flame Detection Using Fuzzy Logic
Hwang, Hyun-Jae ; Ko, Byoung-Chul ;
The KIPS Transactions:PartB, volume 16B, issue 6, 2009, Pages 463~470
DOI : 10.3745/KIPSTB.2009.16B.6.463
In this paper, we propose the advanced fire-flame detection algorithm using camera image for better performance than previous sensors-based systems which is limited on small area. Also, previous works using camera image were depend on a lot of heuristic thresholds or required an additional computation time. To solve these problems, we use statistical values and divide image into blocks to reduce the processing time. First, from the captured image, candidate flame regions are detected by a background model and fire colored models of the fire-flame. After the probability models are formed using the change of luminance, wavelet transform and the change of motion on time axis, they are used for membership function of fuzzy logic. Finally, the result function is made by the defuzzification, and the probability value of fire-flame is estimated. The proposed system has shown better performance when it compared to Toreyin's method which perform well among existing algorithms.
Voice Features Extraction of Lung Diseases Based on the Analysis of Speech Rates and Intensity
Kim, Bong-Hyun ; Cho, Dong-Uk ;
The KIPS Transactions:PartB, volume 16B, issue 6, 2009, Pages 471~478
DOI : 10.3745/KIPSTB.2009.16B.6.471
The lung diseases classifying as one of the six incurable diseases in modern days are caused mostly by smoking and air pollution. Such causes the lung function damages, and results in malfunction of the exchange of carbon dioxide and oxygen in an alveolus, which the interest is augment with risk diseases of life prolongation. With this in the paper, we proposed a diagnosis method of lung diseases by applying parameters of voice analysis aiming at the getting the voice feature extraction. Firstly, we sampled the voice data from patients and normal persons in the same age and sex, and made two sample groups from them. Also, we conducted an analysis by applying the various parameters of voice analysis through the collected voice data. The relational significance between the patient and normal groups can be evaluated in terms of speech rates and intensity as a part of analized parameters. In conclusion, the patient group has shown slower speech rates and bigger intensity than the normal group. With this, we propose the method of voice feature extraction for lung diseases.
Construction Scheme of Training Data using Automated Exploring of Boundary Categories
Choi, Yun-Jeong ; Jee, Jeong-Gyu ; Park, Seung-Soo ;
The KIPS Transactions:PartB, volume 16B, issue 6, 2009, Pages 479~488
DOI : 10.3745/KIPSTB.2009.16B.6.479
This paper shows a reinforced construction scheme of training data for improvement of text classification by automatic search of boundary category. The documents laid on boundary area are usually misclassified as they are including multiple topics and features. which is the main factor that we focus on. In this paper, we propose an automated exploring methodology of optimal boundary category based on previous research. We consider the boundary area among target categories to new category to be required training, which are then added to the target category sementically. In experiments, we applied our method to complex documents by intentionally making errors in training process. The experimental results show that our system has high accuracy and reliability in noisy environment.
A Translation-based Approach to Hierarchical Task Network Planning
Kim, Hyun-Sik ; Shin, Byung-Cheol ; Kim, In-Cheol ;
The KIPS Transactions:PartB, volume 16B, issue 6, 2009, Pages 489~496
DOI : 10.3745/KIPSTB.2009.16B.6.489
Hierarchical Task Network(HTN) planning, a typical planning method for effectively taking advantage of domain-specific control knowledge, has been widely used in complex real applications for a long time. However, it still lacks theoretical formalization and standardization, and so there are some differences among existing HTN planners in terms of principle and performance. In this paper, we present an effective way to translate a HTN planning domain specification into the corresponding standard PDDL specification. Its main advantage is to allow even many domain-independent classical planners to utilize domain-specific control knowledge contained in the HTN specifications. In this paper, we try our translation-based approach to three different domains such as Blocks World, Office Delivery, Hanoi Tower, and then conduct some experiments with a forward-chaining heuristic state-space planner, FF, to analyze the efficiency of our approach.
Automatic Product Feature Extraction for Efficient Analysis of Product Reviews Using Term Statistics
Lee, Woo-Chul ; Lee, Hyun-Ah ; Lee, Kong-Joo ;
The KIPS Transactions:PartB, volume 16B, issue 6, 2009, Pages 497~502
DOI : 10.3745/KIPSTB.2009.16B.6.497
In this paper, we introduce an automatic product feature extracting system that improves the efficiency of product review analysis. Our system consists of 2 parts: a review collection and correction part and a product feature extraction part. The former part collects reviews from internet shopping malls and revises spoken style or ungrammatical sentences. In the latter part, product features that mean items that can be used as evaluation criteria like 'size' and 'style' for a skirt are automatically extracted by utilizing term statistics in reviews and web documents on the Internet. We choose nouns in reviews as candidates for product features, and calculate degree of association between candidate nouns and products by combining inner association degree and outer association degree. Inner association degree is calculated from noun frequency in reviews and outer association degree is calculated from co-occurrence frequency of a candidate noun and a product name in web documents. In evaluation results, our extraction method showed an average recall of 90%, which is better than the results of previous approaches.