• The Journal of the Korea Contents Association
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• v.20 no.1
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• pp.617-629
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• 2020

In the historical and cultural blocks with the most concentrated urban cultural heritage, the development of both side streets is impacted by the development of the main street, which shows a gradual decline. The loss of placeness on both side streets has resulted in more empty houses. Therefore, it is urgent to pay attention and take countermeasures to the empty houses in historical and cultural blocks. In this study, the vacant houses on Zhongshan Road in Hangzhou, China were taken as the object of study to understand the location theory and the six dimensions of Matthew Carmona's urban design. Meanwhile, it further analyzed the evaluative features of the placeness of the vacant houses in the historical and cultural street, to provide direction and basis for the flexible using of other empty houses in Zhongshan Road. Then by applying the Analytic Hierarchy Process (AHP), it obtained the importance scale of each evaluative feature and compared the evaluation results of experts with the analysis results of cases, getting the results as follows: In the flexible application of vacant houses in historical and cultural street, the evaluation result of placeness indicates that this kind of usage should be in order of societal level, perceptional level, functional level, morphological level, visual hierarchy and temporal level; among the evaluative features, security, identity, usability, individuality, aesthetics, connection, diversity, openness, continuity, accessibility, order and history should be considered in turn.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.66-80
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• 2012

It is necessary to normalize spectral image values derived from multi-temporal satellite data to a common scale in order to apply remote sensing methods for change detection, disaster mapping, crop monitoring and etc. There are two main approaches: absolute radiometric normalization and relative radiometric normalization. This study focuses on the multi-temporal satellite image processing by the use of relative radiometric normalization. Three scenes of KOMPSAT-2 imagery were processed using the Multivariate Alteration Detection(MAD) method, which has a particular advantage of selecting PIFs(Pseudo Invariant Features) automatically by canonical correlation analysis. The scenes were then applied to detect disaster areas over Sendai, Japan, which was hit by a tsunami on 11 March 2011. The case study showed that the automatic extraction of changed areas after the tsunami using relatively normalized satellite data via the MAD method was done within a high accuracy level. In addition, the relative normalization of multi-temporal satellite imagery produced better results to rapidly map disaster-affected areas with an increased confidence level.

• Cartoon and Animation Studies
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• s.36
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• pp.349-374
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• 2014

The light is the language. Directors have to describe the scene component effectively his intention to configure the scene as an appropriately. After this act of the character, the layout of the props and scene lights will enter to the scene components. Those things help to audiences can understand narrative of work and emotion that producer want to send. Expressing their emotions especially using the lights by adjusting the colors and contrast makes audience to concentrate on work and understand naturally. This lighting technique clearly appears on early year theaters stage of England and Rembrandt's paintings. Properly dividing and controlling the lights dramatically increases the beauty of the work elements to express a variety of emotions such as worries and fear. Therefore, it can be evolve depending on director's intent of using lights on his work. Lights can increase involvement of human emotion through basic features that cognition of object, visualization of space-time and by artistic method in the product. This study will examine the role and how to use lighting to express the proper sentiment based on the narrative of the work. Making research named "Lighting Research of 3D animated film which applying light features to express emotion" previous study and have to combine emotional vocabulary and emotion-based theory for classifying the emotional language that can be applied on 3D animation. And choosing most emotional scene from 3D animation for analyze how they used lighting to expressing emotions. Directors trying to show up about the light role through light method that matched perfectly with an emotional language. Expecting this research work of directing 3D animations light for expressing emotional feelings will be continue successfully.

• The KIPS Transactions:PartB
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• v.15B no.1
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• pp.25-36
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• 2008

In this paper, we present a robust hand recognition approach to sudden illumination changes. The proposed approach constructs a background model with respect to hue and hue gradient in HSI color space and extracts a foreground hand region from an input image using the background subtraction method. Eighteen features are defined for a hand pose and multi-class SVM(Support Vector Machine) approach is applied to learn and classify hand poses based on eighteen features. The proposed approach robustly extracts the contour of a hand with variations in illumination by applying the hue gradient into the background subtraction. A hand pose is defined by two Eigen values which are normalized by the size of OBB(Object-Oriented Bounding Box), and sixteen feature values which represent the number of hand contour points included in each subrange of OBB. We compared the RGB-based background subtraction, hue-based background subtraction and the proposed approach with sudden illumination changes and proved the robustness of the proposed approach. In the experiment, we built a hand pose training model from 2,700 sample hand images of six subjects which represent nine numerical numbers from one to nine. Our implementation result shows 92.6% of successful recognition rate for 1,620 hand images with various lighting condition using the training model.

• 재활복지
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• v.21 no.3
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• pp.129-146
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• 2017

In an event of an emergency, such as fire in a building, visually impaired and blind people are prone to exposed to a level of danger that is greater than that of normal people, for they cannot be aware of it quickly. Current fire detection methods such as smoke detector is very slow and unreliable because it usually uses chemical sensor based technology to detect fire particles. But by using vision sensor instead, fire can be proven to be detected much faster as we show in our experiments. Previous studies have applied various image processing and machine learning techniques to detect fire, but they usually don't work very well because these techniques require hand-crafted features that do not generalize well to various scenarios. But with the help of recent advancement in the field of deep learning, this research can be conducted to help solve this problem by using deep learning-based object detector that can detect fire using images from security camera. Deep learning based approach can learn features automatically so they can usually generalize well to various scenes. In order to ensure maximum capacity, we applied the latest technologies in the field of computer vision such as YOLO detector in order to solve this task. Considering the trade-off between recall vs. complexity, we introduced two convolutional neural networks with slightly different model's complexity to detect fire at different recall rate. Both models can detect fire at 99% average precision, but one model has 76% recall at 30 FPS while another has 61% recall at 50 FPS. We also compare our model memory consumption with each other and show our models robustness by testing on various real-world scenarios.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.252-263
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• 2016

Road sign is an important street furniture that gives some information such as road conditions, driving direction and condition for a driver. Thus, road sign is a major target of image recognition for self-driving car, ADAS(autonomous vehicle and intelligent driver assistance systems), and ITS(intelligent transport systems). In this paper, an enhanced road sign recognition system is proposed for MMS(Mobile Mapping System) using the single camera and GPS. For the proposed system, first, a road sign recognition scheme is proposed. this scheme is composed of detection and classification step. In the detection step, object candidate regions are extracted in image frames using hybrid road sign detection scheme that is based on color and shape features of road signs. And, in the classification step, the area of candidate regions and road sign template are compared. Second, a Geo-marking scheme for geo-content that is consist of road sign image and coordinate value is proposed. If the serious situation such as car accident is happened, this scheme can protect geographical information of road sign against illegal users. By experiments with test video set, in the three parts that are road sign recognition, coordinate value estimation and geo-marking, it is confirmed that proposed schemes can be used for MMS in commercial area.

• Journal of Environmental Impact Assessment
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• v.24 no.3
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• pp.260-277
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• 2015

The object of this study was the climate change sensitivity assessment of Korean Fir and Khinghan Fir as a representative subalpine plant in South Korea. Using species distribution models, we predicted the probability of current and future species distribution. According to this study, potential distribution that have been predicted based on the threshold (MTSS) is, Khinghan Fir was higher loss rate than Korean Fir. And in the climate change sensitivity assessment using the scalar sensitivity weight ($W_{is}$), $W_{is}$ of Korean Fir was higher relatively than the sensitivity of Khinghan Fir. When using the species distribution models as shown in this study may vary depending on the probability of presence data and spatial variables. Therefore should be prior decision studies on the ecological environment of the study species. Based on this study, if it is domestic applicable climate change sensitivity assessment method is developed. it would be important decision-making to climate change and biological diversity of adaptation policy.

• Korean Journal of Biological Psychiatry
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• v.2 no.2
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• pp.257-265
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• 1995

The object of this study is to apply a chaotic signal analysis method to the EEG research, especially in the aspect of neuropsychiatry, and to get some inspection of the chaotic phenomena according to the brain sites and subjects. We have acquired 21 channel EEG data and one EOG according to the international 10-20 system and calculated the correlation dimension. The subject groups are schizophrenics, bipolar disorder, major depression and normal control. They were all awoke and eye-closed. We have found no distinctive features from our experiments except temporal regions have slightly higher correlation dimension. There is also no specific distinctions between groups. We conjecture that these results are mainly because the subjects were not well controlled. EEG dimension may change in accordance with to the age, sex, medication and the time data were selected to calculate. We have also considered some conditions for a better and more objective research of chaotic analysis to EEG research. Better conditioning and standardizing the calculation of correlation dimension is necessary for the application of the chaotic analysis to neuropsychiatry.

• Journal of the Korean Society of Clothing and Textiles
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• v.36 no.1
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• pp.99-111
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• 2012

This paper investigates the formative features and the historical meaning of the Korean dress collection held in the Horniman Museum in London. The Museum holds eighteen items of Korean dresses donated by Mrs. C. de J. Luxmore in 1948 and by Mrs. Bowra in 1953. Male dresses consist of white silk outer robe (durumagi), a pale violet silk waistcoat (jokki), a jade green silk jacket (jeogori), pale yellow silk trousers (baji), a pair of ankle bands (daenim), a cotton waistband (dae), a silk purse (jumeoni), a rattan under-vest (deungbaeja), a pair of rattan wristlets (deungtosi), a top hat (gat) and a skullcap (tanggeon). Female dresses comprise a jade green silk jacket (jeogori), an ivory silk skirt (chima), a light blue silk petticoat (sokchima), two kinds of white cotton trousers (sokbaji and soksokgot), a pair of silk wristlets (tosi) and a pair of padded socks (beoseon). A Korean dress collection of the Horniman Museum shows a set of ordinary dress items worn by a married couple in the 1930s and the 1940s. Of these items, a silk petticoat (sokchima) and a rattan under-vest (deungbaeja) can be highly evaluated as object resources in the history of Korean dress. The petticoat is a rare and valuable example that represents an early type of modern petticoat that has replaced a traditional petticoat (dansokgot). The rattan under-vest has square neckline and two tiny sleeves similar to a Western cap sleeve. This kind of under-vest is a transitional form shown between under-vest similar to the Korean waistcoat (baeja) and one similar to the Western waistcoat (jokki).