• Journal of the Korea Society of Computer and Information
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• v.17 no.7
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• pp.45-52
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• 2012

In this paper, an crowd density in elevator estimation method based on multi-class Adaboost classifier is proposed. The SOM (Self-Organizing Map) based conventional methods have shown insufficient performance in practical scenarios and have weakness for low reproducibility. The proposed method estimates the crowd density using multi-class Adaboost classifier with texture features, namely, GLDM(Grey-Level Dependency Matrix) or GGDM(Grey-Gradient Dependency Matrix). In order to classify into multi-label, weak classifier which have better performance is generated by modifying a weight update equation of general Adaboost algorithm. The crowd density is classified into four categories depending on the number of persons in the crowd, which can be 0 person, 1-2 people, 3-4 people, and 5 or more people. The experimental results under indoor environment show the proposed method improves detection rate by about 20% compared to that of the conventional method.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.8 no.1
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• pp.47-52
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• 2008

The visual implementation of 3-dimensional national environment is focused by the requirement and importance in the fields such as, urban planing, telecommunication facility deployment plan, railway construction, construction engineering, spatial city development, safety and disaster prevention engineering. The currently used DEM system based on the 2-D digital maps and contour lines has limitation in implementation in reproducing the 3-D spatial city. Currently, the LiDAR data which combines the laser and GPS skill has been introduced to obtain high resolution accuracy in the altitude measurement in the advanced country. In this paper, we first introduce the LiDAR based researches in advanced foreign countries, then we propose the data generation scheme and an solution algorithm for the optimal management of our 3-D spatial u-City construction. For this purpose, LiDAR based height data transformed to DEM, and the realtime unification of the vector via digital image mapping and raster via exactness evaluation is transformed to make it possible to trace the model of generated 3-dimensional model with long distance for 3D u-city model generation.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.9
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• pp.45-53
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• 2015

Adaptive support-weight based algorithm can produce better disparity map compared to generic area-based algorithms and also can be implemented as a realtime system. In this paper, we propose a realtime system based on geodesic support-weight which performs better segmentation of objects in the window. The data scheduling is analyzed for efficient hardware design and better performance and the parallel architecture for weight update which takes the longest delay is proposed. The exponential function is efficiently designed using a simple step function by careful error analysis. The proposed architecture is designed with verilogHDL and synthesized using Donbu Hitek 0.18um standard cell library. The proposed system shows 2.22% of error rate and can run up to 260Mhz (25fps) operation frequency with 182K gates.

• Journal of Korea Game Society
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• v.11 no.1
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• pp.47-57
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• 2011

Mobile based location-based service can normally be classified into four categories according to their dimensions of their screen layout: map-based, bird-eye view based, photo-based, and video-based. Specifically, video-based layout system combining AR technology has a appealing factor to users through the reality-based presence but normally requires sophisticated real-time image matching algorithms to represent the system. This paper provides a new location-based service by introducing mirror world to resolve the problem and implements its prototype. The proposed service does not need such algorithm and will effectively be useful for users to get the reality of the presence for any locations which is regardless of a user's real location.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.13
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• pp.5445-5451
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• 2015

Fascin-1 (FSCN1) is an actin-bundling protein that induces cell membrane protrusions, increases cell motility, and is overexpressed in various human epithelial cancers, including esophageal squamous cell carcinoma (ESCC). We analyzed various protein-protein interactions (PPI) of differentially-expressed genes (DEGs), in fascin knockdown ESCC cells, to explore the role of fascin overexpression. The node-degree distributions indicated these PPI sub-networks to be characterized as scale-free. Subcellular localization analysis revealed DEGs to interact with other proteins directly or indirectly, distributed in multiple layers of extracellular membrane-cytoskeleton/ cytoplasm-nucleus. The functional annotation map revealed hundreds of significant gene ontology (GO) terms, especially those associated with cytoskeleton organization of FSCN1. The Random Walk with Restart algorithm was applied to identify the prioritizations of these DEGs when considering their relationship with FSCN1. These analyses based on PPI network have greatly expanded our comprehension of the mRNA expression profile following fascin knockdown to future examine the roles and mechanisms of fascin action.

• Journal of Korea Multimedia Society
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• v.3 no.4
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• pp.356-364
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• 2000

Block based fast motion estimation algorithm use the fixed search pattern to reduce the search point, and are based on the assumption that the error in the mean absolute error space monotonically decreases to the global minimum. Therefore, in case of many local minima in a search region we are likely to find local minima instead of the global minimum and highly rely on the initial search points. This situation is evident in the motion boundary. In this paper we define the candidate regions within the search region using the motion information of the neighbor blocks and we propose the multiple local search method (MLSM) which search for the solution throughout the candidate regions to reduce the possibilities of isolation to the local minima. In the MLSM we mark the candidate region in the search point map and we avoid to search the candidate regions already visited to reduce the calculation. In the simulation results the proposed method shows more excellent results than that of other gradient based method especially in the search of motion boundary. Especially, in PSNR the proposed method obtains similar estimate accuracy with the significant reduction of search points to that of full search.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.6
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• pp.1194-1199
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• 2009

Stereo vision system is useful method for inferring 3D depth information from two or more images. So it has been the focus of attention in this field for a long time. Stereo matching is the process of finding correspondence points in two or more images. A central problem in a stereo matching is that it is difficult to satisfy both the computation time problem and accuracy at the same time. To resolve this problem, we proposed a new stereo matching technique using weighted cost aggregation. To begin with, we extract the weight in given stereo images based on features. We compute the costs of the pixels in a given window using correlation of weighted color and brightness information. Then, we match pixels in a given window between the reference and target images of a stereo pair. To demonstrate the effectiveness of the algorithm, we provide experimental data from several synthetic and real scenes. The experimental results show the improved accuracy of the proposed method.

• The Transactions of the Korea Information Processing Society
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• v.6 no.8
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• pp.2262-2270
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• 1999

In this paper, we describe gesture recognition algorithm using computer vision sensor and HMM. The automatic hand region extraction has been proposed for initializing the tracking of the tele-operation gestures. For this, distance informations(disparity map) as results of stereo matching of initial left and right images are employed to isolate the hand region from a scene. PDOE(positive difference of edges) feature images adapted here have been found to be robust against noise and background brightness. The KNU/KAERI(K/K) gesture instruction set is defined for tele-operation in atomic electric power stations. The composite recognition model constructed by concatenating three gesture instruction models including pre-orders, basic orders, and post-orders has been proposed and identified by discrete HMM. Our experimental results showed that consecutive orders composed of more than two ones are correctly recognized at the rate of above 97%.

• The Journal of the Korea Contents Association
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• v.11 no.11
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• pp.492-502
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• 2011

20 fossil sites of numerous fossil sites in Korea have been designated as Natural Monument for protection and conservation. Many of the sites which is located at the coastal area have been gradually disfigured by natural weathering, erosion and human activity. Thus the conservation of the original form and the documentation for the original figure are necessary. In this study, we applied 3D digital documentation to Natural Monument No. 394, Haenam Uhangri dinosaur, pterosaur, and bird footprint fossil site, for maintaining the original form of the dinosaur footprints. We were able to obtain the 3D digital data on two dinosaur footprint sites, a high resolution distributional map, and more accurate digital data of the dinosaur footprints applied the rendering method by ambient occlusion. 3D digital data on the dinosaur footprints is worth for the conservation and research data, moreover content for applying to the various fields such as to make 3D brochure, interactive contents, and so on.

• Korean Journal of Remote Sensing
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• v.35 no.6_4
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• pp.1341-1350
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• 2019

This research deals with algorithm for forest fire severity classification using multi-temporal KOMPSAT-3A image to mapping forest fire areas. The recent satellite of the KOMPSAT series, KOMPSAT-3A, demonstrates high resolution and multi-spectral imagery with infrared and high resolution electro-optical bands. However, there is a lack of research to classify forest fire severity using KOMPSAT-3A. Therefore, the purpose of this study is to analyze forest fire severity using KOMPSAT-3A images. In addition, this research used pre-fire and post-fire Sentinel-2 with differenced Normalized Burn Ratio (dNBR) to taking for burn severity distribution map. To test the effectiveness of the proposed procedure on April 4, 2019, Gangneung wildfires were considered as a case study. This research used the probability density function for the classification of forest fire damage severity based on R software, a free software environment of statistical computing and graphics. The burn severities were estimated by changing NDVI before and after forest fire. Furthermore, standard deviation of probability density function was used to calculate the size of each class interval. A total of five distribution of forest fire severity were effectively classified.