• Journal of Korea Game Society
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• v.2 no.1
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• pp.49-54
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• 2002

In this paper we propose the methodology for 3D background image construction in computer games. This methodology was developed based on TIP (Tour Into the Picture) using a vanishing line Proposed by Kang et at. The methodology Proposed in this study can simply implement a 3D background for a computer game with a background model which is very complex or based on a real picture. Compared to the graphics technologies generally used, the proposed methodology does not need the process of modeling elaborate 3D information of a background, and hence can display the background even on a low grade personal computer using a small reference image. TIP technology was successfully applied to the implementation of a background model for a computer game and was found to be appropriate especially for real time games.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.1
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• pp.157-165
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• 2011

It is challenging to detect foreground objects when background includes an illumination variation, shadow or structural variation due to its motion. Basically pixel-based background models including codebook-based modeling suffer from statistical randomness of each pixel. This paper proposes an algorithm that incorporates Markov random field model into pixel-based background modeling to achieve more accurate foreground detection. Under the assumptions the distance between the pixel on the input imaging and the corresponding background model and the difference between the scene estimates of the spatio-temporally neighboring pixels are exponentially distributed, a recursive approach for estimating the MRF regularizing parameters is proposed. The proposed method alternates between estimating the parameters with the intermediate foreground detection and estimating the foreground detection with the estimated parameters, after computing it with random initial parameters. Extensive experiment is conducted with several videos recorded both indoors and outdoors to compare the proposed method with the standard codebook-based algorithm.

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.6
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• pp.459-463
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• 2009

Background modeling and motion detection is the one of the most significant real time video processing technique. Until now, many researches are conducted into the topic but it still needs much time for robustness. It is more important when other algorithms are used together such as object tracking, classification or behavior understanding. In this paper, we propose efficient multi-modal background modeling methods which can be understood as simplified learning method of Gaussian mixture model. We present its validity using numerical methods and experimentally show detecting performance.

• Geosystem Engineering
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• v.21 no.5
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• pp.262-272
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• 2018

The U-statistic method is one of the most important structural methods to separate the anomaly from background. It considers the location of samples and carries out the statistical analysis of the data without judging from a geochemical point of view and tries to separate subpopulations and determine anomalous areas. In the present study, 3D U-statistic method has been applied for the first time through the three-dimensional (3D) modeling of an ore deposit. In order to achieve this purpose, 3D U-statistic is applied on the data (Fe grade) resulted from the drilling network in Baghak mine, central part of the Sangan iron mines (in Khorassan Razavi Province, Iran). Afterward, results from applying 3D U-statistic method are used for 3D modeling of the iron mineralization. Results show that the anomalous values are well separated from background so that the determined samples as anomalous are not dispersed and according to their positioning, denser areas of anomalous samples could be considered as anomaly areas. And also, final results (3D model of iron mineralization) show that output model using this method is compatible with designed model for mining operation. Moreover, seen that U-statistic method in addition for separating anomaly from background, could be very efficient for the 3D modeling of different ore type.

• Journal of the Korea Society of Computer and Information
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• v.16 no.4
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• pp.73-81
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• 2011

In this paper, an improved block-based background modeling technique using adaptive parameter estimation that judiciously adjusts the number of model histograms at each frame sequence is proposed. The conventional block-based background modeling method has a fixed number of background model histograms, resulting to false negatives when the image sequence has either rapid illumination changes or swiftly moving objects, and to false positives with motionless objects. In addition, the number of optimal model histogram that changes each type of input image must have found manually. We demonstrate the proposed method is promising through representative performance evaluations including the background modeling in an elevator environment that may have situations with rapid illumination changes, moving objects, and motionless objects.

• Geophysics and Geophysical Exploration
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• v.8 no.3
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• pp.207-217
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• 2005

We present a new approximate formulation of the integral equation (IE) method for models with variable background conductivity. This method overcomes the standard limitation of the conventional If method related to the use of a horizontally layered background only. The new approximate IE method still employs the Green's functions for a horizontally layered 1-D model. However, the new method allows us to use an inhomogeneous background with the IE method. The method was carefully tested for modeling the EM field for complex structures with a known variable background conductivity. It can find wide application in modeling EM data for multiple geological models with some common geoelectrical features, like a known inhomogeneous overburden, or salt dome structures.

• Korean Journal of Child Studies
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• v.28 no.5
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• pp.127-141
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• 2007

The purpose of this research was to analyze the trajectory of child's academic attainment and the effect of family socioeconomic background on the trajectory. Data were part of the Korea Youth Panel Survey 2003-2005(Middle School 2) and were analyzed by Latent Growth Curve Modeling(LGM). The degree of child's academic attainment decreased over 3 years. Socioeconomic status variables that influenced academic trajectory were family poverty, parent's attainments in scholarship, and family structure. Findings from this study suggest that societal support for low socioeconomic status families is needed for improvement of academic attainment of their children.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.197-202
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• 2007

Most of seismic reflection prospecting assumes subsurface formation to be homogeneous media. These models are not capable of estimating small scale heterogeneity which is verified by well log data or drilling core. And those synthetic seismograms by homogeneous media are limited to explain various changes at field data. So we developed a inhomogeneous velocity model which can estimate inhomogeneity of background medium to implement numerical modeling from homogeneous medium and inhomogeneous medium on the model. Background medium using three autocorrelation functions in order to generate inhomogeneous velocity media was according to dominant wavelength of background medium and correlation length of random medium. And then we compared shot gathers. The results show that numerical modeling implemented at inhomogeneous medium depicts complex wave propagation of field data.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.125-138
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• 2020

Due to the development of camera technology, the cost of producing time-lapse video has been reduced, and time-lapse videos are being applied in many fields. Time-lapse video is created using images obtained by shooting for a long time at long intervals. In this paper, we propose a method to improve the quality of time-lapse videos monitoring the changes in plants. Considering the characteristics of time-lapse video, we propose a method of separating the desired and unnecessary objects and removing unnecessary elements. The characteristic of time-lapse videos that we have noticed is that unnecessary elements appear intermittently in the captured images. In the proposed method, noises are removed by applying a codebook background modeling algorithm to use this characteristic. Experimental results show that the proposed method is simple and accurate to find and remove unnecessary elements in time-lapse videos.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.238-244
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• 2013

In energy dispersive X-ray fluorescence analysis, the removal of the continuum on which the X-ray spectrum is superimposed is one of the most important processes, since it has a strong influence on the analysis result. The existing methods which have been used for it usually require tight constraints or prior information on the continuum. In this paper, an efficient background correction method is proposed for Energy Dispersive X-ray fluorescence (EDXRF) spectra. The proposed method has two steps of background modeling and background correction. It is based on the basic concept which differentiates background areas from the peak areas in a spectrum and the SNIP algorithm, one of the popular methods for background removal, is used to enhance the performance. After detecting some points which belong to the background from a spectrum, its background is modeled by a curve fitting method based on them. And then the obtained background model is subtracted from the raw spectrum. The method has been shown to give better results than some of traditional methods, while working under relatively weak constraints or prior information.