• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1189-1196
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• 2023

Due to the acceleration of urbanization and advancements in technology, the importance of information related to indoor spaces has been increasing. Various scanning technologies are being developed to enable versatile utilization of the interior of buildings. In this paper, a system is proposed that utilizes 2D LIDAR for scanning, rotating, and moving LIDAR in the vertical direction to obtain a collection of 2D data, which is then aggregated to acquire 3D indoor spatial information. Finally, algorithms, including error correction, are applied to visualize the indoor structure in three dimensions and generate an output.

• Journal of Internet Computing and Services
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• v.16 no.3
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• pp.21-32
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• 2015

Since spatio-temporal local features for video representation have become an important issue of modeless bottom-up approaches in action recognition, various methods for feature extraction and description have been proposed in many papers. In particular, BoF(bag of features) has been promised coherent recognition results. The most important part for BoF is how to represent dynamic information of actions in videos. Most of existing BoF methods consider the video as a spatio-temporal volume and describe neighboring 3D interest points as complex volumetric patches. To simplify these complex 3D methods, this paper proposes a novel method that builds BoF representation as a way to learn 2D interest points directly from video data. The basic idea of proposed method is to gather feature points not only from 2D xy spatial planes of traditional frames, but from the 2D time axis called spatio-temporal frame as well. Such spatial-temporal features are able to capture dynamic information from the action videos and are well-suited to recognize human actions without need of 3D extensions for the feature descriptors. The spatio-temporal BoF approach using SIFT and SURF feature descriptors obtains good recognition rates on a well-known actions recognition dataset. Compared with more sophisticated scheme of 3D based HoG/HoF descriptors, proposed method is easier to compute and simpler to understand.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.389-393
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• 2007

There has been many researches using LiDAR(Light Detection And Ranging) data. There has been many other researches through out the world using the 3 dimensional spatial data in various fields. In this research, Using lidar data and digital images, we have extracted the position of the power-transmission line and created 3 dimensional models. The presented method is more efficient than field surveying and it can also be used lot monitoring change in the environment

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.38 no.1
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• pp.43-48
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• 2020

Open pit mines for limestone mining require rapid development of technologies and efforts to prevent safety accidents due to rapid deterioration of the slope due to deforestation and rapid changes in the topography. Accurate three-dimensional spatial information on the terrain should be the basis for reducing environmental degradation and safe development of open pit mines. Therefore, this study constructed spatial information about open pit mine using UAV(Unmanned Aerial Vehicle) and analyzed its utility. images and 3D laser scan data were acquired using UAV, and digital surface model, digital elevation model and ortho image were generated through data processing. DSM(Digital Surface Model) and ortho image were constructed using image obtained from UAV. Trees were removed using 3D laser scan data and numerical elevation models were produced. As a result of the accuracy analysis compared with the check points, the accuracy of the digital surface model and the digital elevation model was about 11cm and 8cm, respectively. The use of three-dimensional geospatial information in the mineral resource development field will greatly contribute to effective mine management and prevention of safety accidents.

• Journal of the Korean earth science society
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• v.32 no.6
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• pp.560-574
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• 2011

Satellite images that have been obtained periodically and continuously are very effective data to monitor the changes of Earth's surface. Traditionally, the studies on change detection using satellite images have mainly focused on comparison between two results after analyzing two images respectively. However, the interests in researches to catch smooth trends and short duration events from continual multi-temporal images have been increased recently. In this study, we introduce and test an approach based on 3D wavelet transform to analyze the multi-temporal satellite images. 3D wavelet transform can reduce the dimensions of data conserving main trends. Also, it is possible to extract important patterns and to analyze spatial and temporal relations with neighboring pixels using 3D wavelet transform. As a result, 3D wavelet transform is useful to capture the long term trends and short-term events rapidly. In addition, we can expect to get new information through sub-bands of 3D wavelet transform which provide different information by decomposed direction.

• Journal of the Korean Institute of Landscape Architecture
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• v.23 no.3
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• pp.155-166
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• 1995

The aim of this paper was to investigate images of neighborhood parks and pergola facilities. 280 individuals responded to the 19 semantic differential pollar terms for all four parks. A 7-point semantic differential scale was used. Results from the data analysis suggest several important findings; 1. Mean scores were significantly different in most of S.D.scales according to park and pergola facilities types. As compared with park, S.D.scales values of pergola varied with its visual identity in the spatial composition of park. 2. Data from the factor analysis revealed that four dimensions appeared for all park and pergola types : "Evaluation ", "Potentiality", "Variety", and "Familiarity". 3. In terms of the "Familiarity" dimension, Omok park and its pergola were viewed a ssignificantly more familiar than any of the other three areas. 4. Parks were perceived more positive than pergolas images in the dimensions of "Evaluation ", "Variety", and "Familiarity". 5. Regression analysis showed that "Evaluation "and "Variety" dimensions were mainly related to visual preference.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.4C
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• pp.533-540
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• 2004

This paper proposes a new multispectral image data compression algorithm that can efficiently reduce spatial and spectral redundancies by applying classified prediction, a Karhunen-Loeve transform (KLT), and the three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm in the wavelet transform (WT) domain. The classification is performed in the WT domain to exploit the interband classified dependency, while the resulting class information is used for the interband prediction. The residual image data on the prediction errors between the original image data and the predicted image data is decorrelated by a KLT. Finally, the 3-D SPIHT algorithm is used to encode the transformed coefficients listed in a descending order spatially and spectrally as a result of the WT and KLT. Simulation results showed that the reconstructed images after using the proposed algorithm exhibited a better quality and higher compression ratio than those using conventional algorithms.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.209-218
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• 2009

3D backprojection is a kind of reconstruction algorithm to generate volume data consisting of tomographic images, which provides spatial information of the original 3D data from hundreds of 2D projections. The computational time of backprojection increases in proportion to the size of volume data and the number of projection images since the value of every voxel in volume data is calculated by considering corresponding pixels from hundreds of projections. For the reduction of computational time, fast GPU based 3D backprojection methods have been studied recently and the performance of them has been improved significantly. This paper presents two multiple GPU based methods to maximize the parallelism of GPU and compares the efficiencies of two methods by considering both the number of projections and the size of volume data. The first method is to generate partial volume data independently for all projections after allocating a half size of volume data on each GPU. The second method is to acquire the entire volume data by merging the incomplete volume data of each GPU on CPU. The in-complete volume data is generated using the half size of projections after allocating the full size of volume data on each GPU. In experimental results, the first method performed better than the second method when the entire volume data can be allocated on GPU. Otherwise, the second method was efficient than the first one.

• The KSFM Journal of Fluid Machinery
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• v.10 no.4
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• pp.47-54
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• 2007

Simultaneous 3-D LDV measurements of the in-cylinder flows of three different engine setups were summarized for the quantification of the flow characteristics in each vertical or horizontal plane, and in entire cylinder volume. The ensemble averaged-velocity, tumble and swirl motions, and turbulent kinetic energy during the intake and compression strokes were examined from the measured velocity data (approximately 2,000 points for each engine setup). The better spatial resolution of the 3-D LDV allows measurements of the instantaneous flow structures, yielding more valuable information about the smaller flow structures and the cycle-to-cycle variation of these flow patterns. Tumble and swirl ratios, and turbulent kinetic energy were quantified as planar and volumetric quantities. The measurements and calculation results were animated for the visualization of the flow, and hence ease to analysis.

• Proceedings of the KIEE Conference
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• 2003.11c
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• pp.777-780
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• 2003

We have tried to create a vision system like human eye for a long time. We have obtained some distinguished results through many studies. Stereo vision is the most similar to human eye among those. This is the process of recreating 3-D spatial information from a pair of 2-D images. In this paper, we have designed a stereo matching algorithm based on systolic array architecture using edges and pixel data. This is more advanced vision system that improves some problems of previous stereo vision systems. This decreases noise and improves matching rate using edges and pixel data and also improves processing speed using high integration one chip FPGA and compact modules. We can apply this to robot vision and automatic control vehicles and artificial satellites.