• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.3 s.303
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• pp.39-52
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• 2005

In this paper, a registration method is presented to register partial 3D point clouds, acquired from a multi-view camera, for 3D reconstruction of an indoor environment. In general, conventional registration methods require a high computational complexity and much time for registration. Moreover, these methods are not robust for 3D point cloud which has comparatively low precision. To overcome these drawbacks, a projection-based registration method is proposed. First, depth images are refined based on temporal property by excluding 3D points with a large variation, and spatial property by filling up holes referring neighboring 3D points. Second, 3D point clouds acquired from two views are projected onto the same image plane, and two-step integer mapping is applied to enable modified KLT (Kanade-Lucas-Tomasi) to find correspondences. Then, fine registration is carried out through minimizing distance errors based on adaptive search range. Finally, we calculate a final color referring colors of corresponding points and reconstruct an indoor environment by applying the above procedure to consecutive scenes. The proposed method not only reduces computational complexity by searching for correspondences on a 2D image plane, but also enables effective registration even for 3D points which have low precision. Furthermore, only a few color and depth images are needed to reconstruct an indoor environment.

• Korean Journal of Radiology
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• v.19 no.6
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• pp.1179-1186
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• 2018

Objective: The purposes of this study were to evaluate size-specific dose estimate (SSDE) of low-dose CT (LDCT) in the Korean Lung Cancer Screening (K-LUCAS) project and to determine whether CT protocols from Western countries are appropriate for lung cancer screening in Korea. Materials and Methods: For participants (n = 256, four institutions) of K-LUCAS pilot study, volume CT dose index ($CTDI_{vol}$) using a 32-cm diameter reference phantom was compared with SSDE, which was recalculated from $CTDI_{vol}$ using size-dependent conversion factor (f-size) based on the body size, as described in the American Association of Physicists in Medicine Report 204. This comparison was subsequently assessed by body mass index (BMI) levels (underweight/normal vs. overweight/obese), and automatic exposure control (AEC) adaptation (yes/no). Results: Size-specific dose estimate was higher than $CTDI_{vol}$ ($2.22{\pm}0.75mGy$ vs. $1.67{\pm}0.60mGy$, p < 0.001), since the f-size was larger than 1.0 for all participants. The ratio of SSDE to $CTDI_{vol}$ was higher in lower BMI groups; 1.26, 1.37, 1.43, and 1.53 in the obese (n = 103), overweight (n = 70), normal (n = 75), and underweight (n = 4), respectively. The ratio of SSDE to $CTDI_{vol}$ was greater in standard-sized participants than in large-sized participants independent of AEC adaptation; with AEC, SSDE/$CTDI_{vol}$ in large- vs. standard-sized participants: $1.30{\pm}0.08$ vs. $1.44{\pm}0.08$ (p < 0.001) and without AEC, $1.32{\pm}0.08$ vs. $1.42{\pm}0.06$ (p < 0.001). Conclusion: Volume CT dose index based on a reference phantom underestimates radiation exposure of LDCT in standard-sized Korean participants. The optimal radiation dose limit needs to be verified for standard-sized Korean participants.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.475-491
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• 2021

With the recent increase in available high-resolution (< ~1 m) satellite SAR images, the demand for precise registration of SAR images is increasing in various fields including change detection. The registration between high-resolution SAR images acquired in different look angle is difficult due to speckle noise and geometric distortion caused by the characteristics of SAR images. In this study, registration is performed in two stages, coarse and fine, using the x-band SAR data imaged at staring spotlight mode of TerraSAR-X. For the coarse registration, a method combining the adaptive sampling method and SAR-SIFT (Scale Invariant Feature Transform) is applied, and three rigid methods (NCC: Normalized Cross Correlation, Phase Congruency-NCC, MI: Mutual Information) and one non-rigid (Gefolki: Geoscience extended Flow Optical Flow Lucas-Kanade Iterative), for the fine registration stage, was performed for performance comparison. The results were compared by using RMSE (Root Mean Square Error) and FSIM (Feature Similarity) index, and all rigid models showed poor results in all image combinations. It is confirmed that the rigid models have a large registration error in the rugged terrain area. As a result of applying the Gefolki algorithm, it was confirmed that the RMSE of Gefolki showed the best result as a 1~3 pixels, and the FSIM index also obtained a higher value than 0.02~0.03 compared to other rigid methods. It was confirmed that the mis-registration due to terrain effect could be sufficiently reduced by the Gefolki algorithm.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.153-161
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• 2021

This study analyzed the ripple effect of the demand-side support for start-up venture companies on the macro economy using Dynamic General Equilibrium model. In the model, start-up venture companies were expressed in a manner that distinguished between workers and entrepreneurs by applying the span of control in the Lucas(1978). As a result of the analysis, when the share of public procurement of start-up venture companies was increased from 5.7% to 10%, the actual production of start-up venture companies increased by about 46.17% and the number of venture companies increased by about 150%. In addition, it was analyzed that the number of jobs through venture companies increased by about 61.56%. In addition, it was found that the economic effect was greatly reduced when the start-up venture company was supported as a subsidy for the supply sector with the same amount as the public procurement support. This is interpreted as the fact that if the government implements the supply-side support policy, the expansion of supply causes the price of start-up venture companies to fall, reducing the effect of the support policy in half. Therefore, when supporting start-up venture companies, the government should make efforts to maximize the policy effect by expanding the demand-side support through public procurement and reducing the payment of simple subsidies to start-up venture companies.

• International Journal of Control, Automation, and Systems
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• v.5 no.4
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• pp.436-443
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• 2007

In this paper, an intelligent method called BELBIC (Brain Emotional Learning Based Intelligent Controller) is used to control of Locally Linear Neuro-Fuzzy Model (LOLIMOT) of Washing Machine. The Locally Linear Neuro-Fuzzy Model of Washing Machine is obtained based on previously extracted data. One of the important issues in using BELBIC is its parameters setting. On the other hand, the controller design for Washing Machine is a multi objective problem. Indeed, the two objectives, energy consumption and effectiveness of washing process, are main issues in this problem, and these two objectives are in contrast. Due to these challenges, a Multi Objective Genetic Algorithm is used for tuning the BELBIC parameters. The algorithm provides a set of non-dominated set points rather than a single point, so the designer has the advantage of selecting the desired set point. With considering the proper parameters after using additional assumptions, the simulation results show that this controller with optimal parameters has very good performance and considerable saving in energy consumption.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.24-32
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• 2006

본 논문에서는 다시점 카메라부터 획득된 부분적인 3D 점군을 사용하여 실내환경의 3D 복원을 위한 새로운 방법을 제안한다. 지금까지 다양한 양안차 추정 알고리즘이 제안되었으며, 이는 활용 가능한 깊이 영상이 다양함을 의미한다. 따라서, 본 논문에서는 일반화된 다시점 카메라를 이용하여 실내환경을 복원하는 방법을 다룬다. 첫 번째, 3D 점군들의 시간적 특성을 기반으로 변화량이 큰 3D 점들을 제거하고, 공간적 특성을 기반으로 주변의 3D 점을 참조하여 빈 영역을 채움으로써 깊이 영상 정제 과정을 수행한다. 두 번째, 연속된 두 시점에서의 3D 점군을 동일한 영상 평면으로 투영하고, 수정된 KLT (Kanade-Lucas-Tomasi) 특징 추적기를 사용하여 대응점을 찾는다. 그리고 대응점 간의 거리 오차를 최소화함으로써 정밀한 정합을 수행한다. 마지막으로, 여러 시점에서 획득된 3D 점군과 한 쌍의 2D 영상을 동시에 이용하여 3D 점들의 위치를 세밀하게 조절함으로써 최종적인 3D 모델을 생성한다. 제안된 방법은 대응점을 2D 영상 평면에서 찾음으로써 계산의 복잡도를 줄였으며, 3D 데이터의 정밀도가 낮은 경우에도 효과적으로 동작한다. 또한, 다시점 카메라를 이용함으로써 수 시점에서의 깊이 영상과 컬러 영상만으로도 실내환경 3D 복원이 가능하다. 제안된 방법은 네비게이션 뿐만 아니라 상호작용을 위한 3D 모델 생성에 활용될 수 있다.

• Journal of Korea Multimedia Society
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• v.15 no.4
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• pp.449-471
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• 2012

In intelligent surveillance systems, it is required to robustly track multiple people. Most of the previous studies adopted a Gaussian mixture model (GMM) for discriminating the object from the background. However, it has a weakness that its performance is affected by illumination variations and shadow regions can be merged with the object. And when two foreground objects overlap, the GMM method cannot correctly discriminate the occluded regions. To overcome these problems, we propose a new method of tracking and identifying multiple people. The proposed research is novel in the following three ways compared to previous research: First, the illuminative variations and shadow regions are reduced by an illumination normalization based on the median and inverse filtering of the L*a*b* image. Second, the multiple occluded and overlapped people are tracked by combining the GMM in the still image and the Lucas-Kanade-Tomasi (LKT) method in successive images. Third, with the proposed human tracking and the existing face detection & recognition methods, the tracked multiple people are successfully identified. The experimental results show that the proposed method could track and recognize multiple people with accuracy.

• Journal of the Korean Operations Research and Management Science Society
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• v.3 no.1
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• pp.81-91
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• 1978

Decision models are an attempt to reduce uncertainty in the decision making process. The models describe the relationships of variables and given proper input data generate solutions to managerial problems. These solutions may not be answers to the problems for one of two reasons. First, the data input into the model may not be consistant with the underlying assumptions of the model being used. Frequently parameters are assumed to be deterministic when in fact they are probabilistic in nature. The second failure is that often the decision maker recognizes that the data available are not appropriate for the model being used and begins to collect the required data. By the time these data has been compiled the solution is no longer an answer to the problem. This relates to the timeliness of decision making. The authors point out throught the use of an illustrative problem that stocastic models are well developed and that they do not suffer from any lack of mathematical exactiness. The primary problem is that generally accepted procedures for data generation are historical in nature and not relevant for probabilistic decision models. The authors advocate that management information system designers and accountants must become more familiar with these decision models and the input data required for their effective implementation. This will provide these professionals with the background necessary to generate data in a form that makes it relevant and timely for the decision making process.

• The Journal of Korea Robotics Society
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• v.10 no.3
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• pp.171-177
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• 2015

A telerobot offers a more engaging and enjoyable interaction with people at a distance by communicating via audio, video, expressive gestures, body pose and proxemics. To provide its potential benefits at a reasonable cost, this paper presents a telepresence robot system for video communication which can deliver speaker's head motion through its display stanchion. Head gestures such as nodding and head-shaking can give crucial information during conversation. We also can assume a speaker's eye-gaze, which is known as one of the key non-verbal signals for interaction, from his/her head pose. In order to develop an efficient head tracking method, a 3D cylinder-like head model is employed and the Harris corner detector is combined with the Lucas-Kanade optical flow that is known to be suitable for extracting 3D motion information of the model. Especially, a skin color-based face detection algorithm is proposed to achieve robust performance upon variant directions while maintaining reasonable computational cost. The performance of the proposed head tracking algorithm is verified through the experiments using BU's standard data sets. A design of robot platform is also described as well as the design of supporting systems such as video transmission and robot control interfaces.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.62 no.1
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• pp.18-22
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• 2013

This paper describes the information for quantitative simulation of weakly ionized plasma. We must grasp the meaning of the plasma state condition to utilize engineering application and to understand materials of plasma state. Using quantitative simulations of weakly ionized plasma, we can analyze gas characteristic. In this paper, the electron transport characteristic in $CH_4$ has been analysed over the E/N range 0.1~300[Td], at the 300[$_{\circ}\;K$] by the two term approximation Boltzmann equation method and Monte Carlo Simulation. Boltzmann equation method has also been used to predict swarm parameter using the same cross sections as input. The behavior of electron has been calculated to give swarm parameter for the electron energy distribution function has been analysed in $CH_4$ at E/N=10, 100 for a case of the equilibrium region in the mean energy. A set of electron collision cross section has been assembled and used in Monte Carlo simulation to predict values of swarm parameters. The result of Boltzmann equation and Monte Carlo Simulation has been compared with experimental data by Ohmori, Lucas and Carter. The swarm parameter from the swarm study are expected to sever as a critical test of current theories of low energy scattering by atoms and molecules.