• Communications for Statistical Applications and Methods
• /
• 제9권2호
• /
• pp.389-399
• /
• 2002

In order to examine whether the difference between two point estimates of population proportions is statistically significant, data analysts use two techniques. The first is to explore the overlap between two associated confidence intervals. Second method is to test the significance which is introduced at most statistical textbooks under the common assumptions of consistency, asymptotic normality, and asymptotic independence of the estimates. Under the null hypothesis which is two population proportions are equal, the pooled estimator of population proportion is preferred as a point estimator since two independent random samples are considered to be collected from one population. Hence as an alternative method, we could obtain another confidence interval of the difference of the population proportions with using the pooled estimate. We conclude that, among three methods, the overlapped method is under-estimated, and the difference of the population proportions method is over-estimated on the basis of the proposed method.

• ETRI Journal
• /
• 제39권2호
• /
• pp.181-190
• /
• 2017

The movements of the human body are difficult to capture owing to the complexity of the three-dimensional skeleton model and occlusion problems. In this paper, we propose a motion capture system that tracks dynamic human motions in real time. Without using external markers, the proposed system adopts multiple depth sensors (Microsoft Kinect) to overcome the occlusion and body rotation problems. To combine the joint data retrieved from the multiple sensors, our calibration process samples a point cloud from depth images and unifies the coordinate systems in point clouds into a single coordinate system via the iterative closest point method. Using noisy skeletal data from sensors, a posture reconstruction method is introduced to estimate the optimal joint positions for consistent motion generation. Based on the high tracking accuracy of the proposed system, we demonstrate that our system is applicable to various motion-based training programs in dance and Taekwondo.

• Journal of Ecology and Environment
• /
• 제41권2호
• /
• pp.34-44
• /
• 2017

Background: Monitoring terrestrial vegetation cover condition is important to evaluate its current condition and to identify potential vulnerabilities. Due to simplicity and low cost, point intercept method has been widely used in evaluating grassland surface and quantifying cover conditions. Field-based digital photography method is gaining popularity for the purpose of cover estimate, as it can reduce field time and enable additional analysis in the future. However, the caveats and uncertainty among field-based vegetation cover estimation methods is not well known, especially across a wide range of cover conditions. We compared cover estimates from point intercept and digital photography methods with varying sampling intensities (25, 49, and 100 points within an image), across 61 transects in typical steppe, forest steppe, and desert steppe in central Mongolia. We classified three photosynthetic groups of cover important to grassland ecosystem functioning: photosynthetic vegetation, non-photosynthetic vegetation, and bare soil. We also acquired normalized difference vegetation index from satellite image comparison with the field-based cover. Results: Photosynthetic vegetation estimates by point intercept method were correlated with normalized difference vegetation index, with improvement when non-photosynthetic vegetation was combined. For digital photography method, photosynthetic and non-photosynthetic vegetation estimates showed no correlation with normalized difference vegetation index, but combining of both showed moderate and significant correlation, which slightly increased with greater sampling intensity. Conclusions: Results imply that varying greenness is playing an important role in classification accuracy confusion. We suggest adopting measures to reduce observer bias and better distinguishing greenness levels in combination with multispectral indices to improve estimates on dry matter.

• 제어로봇시스템학회논문지
• /
• 제13권3호
• /
• pp.224-229
• /
• 2007

This paper presents a camera calibration method using several images for three dimensional measurement applications such as stereo systems, mobile robots, and visual inspection systems in factories. Conventional calibration methods that use single image suffer from errors related to reference point extraction in image, lens distortion, and numerical analysis of nonlinear optimization. The camera parameter values obtained from images of same camera is not same even though we use same calibration method. The camera parameters that are obtained from several images of different view for a calibration target is usaully not same with large error values and we can not assume a special probabilistic distribution when we estimate the parameter values. In this paper, the median value of camera parameters from several images is used to improve estimation of the camera values in an iterative step with nonlinear optimization. The proposed method is proved by experiments using real images.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2002년도 ICCAS
• /
• pp.79.4-79
• /
• 2002

Our goal is the development of a system that estimates the location of interested point in a room with accuracy and low cost. Non-contacting position estimating method is widely used in various areas. Among these methods, acoustic signal-based method is the cheapest and provides reasonably accurate estimation as a result of many research efforts. Most of the acoustic-signal-based three-dimensional location estimators such as 3D sonic digitizer are using the ultrasound, and are organized with two procedures; time-of-flight (TOF) estimation and localization estimation. Since the errors in estimating the TOF could be accumulated with that of localization estimate, accuracy of TOF estimate is as...

• 디지털융복합연구
• /
• 제14권11호
• /
• pp.319-324
• /
• 2016

실내에서 카메라를 이용한 로봇 응용이나 가상현실(Virtual Reality) 응용의 경우 평면을 찾고 추정하는 기술은 매우 중요한 기술이다. RGB-D 카메라의 경우 실내의 평면에서 질감 정보가 없는 평면에서도 3차원 관측 데이터를 얻을 수 있지만, 이미지 영역에서 점군 데이터(Point-cloud Data)를 처리하기 위해서는 많은 연산량이 필요하다. 더군다나 현재 관측되고 있는 평면의 개수가 몇 개인지 미리 알 수 없으며, 평면으로 검출(Plane Detection) 하더라도 강인하게 3차원에서 평면을 추정(Plane Estimation)하려면 추가적인 연산이 필요하다. 본 논문에서는 연속 데이터를 이용해 실시간으로 평면의 개수를 선택하며 평면을 추정하는 방법을 제시하고자 한다. 실험 결과를 통해 제안하는 방법이 전체 데이터를 처리하는 것에 비해 약 22배의 속도 개선을 가져 올 수 있음을 보였다.

• 대기
• /
• 제26권4호
• /
• pp.697-709
• /
• 2016

This study estimates and evaluates the extreme value of 30 m-resolution daily maximum and minimum temperatures over South Korea, using inverse distance weighting (IDW), parameter-elevation regression on independent slopes model (PRISM) and generalized extreme value (GEV) method. The three experiments are designed and performed to find the optimal estimation strategy to obtain extreme value. First experiment (EXP1) applies GEV firstly to automated surface observing system (ASOS) to estimate extreme value and then applies IDW to produce high-resolution extreme values. Second experiment (EXP2) is same as EXP1, but using PRISM to make the high-resolution extreme value instead of IDW. Third experiment (EXP3) firstly applies PRISM to ASOS to produce the high-resolution temperature field, and then applies GEV method to make high resolution extreme value data. By comparing these 3 experiments with extreme values obtained from observation data, we find that EXP3 shows the best performance to estimate extreme values of maximum and minimum temperatures, followed by EXP1 and EXP2. It is revealed that EXP1 and EXP2 have a limitation to estimate the extreme value at each grid point correctly because the extreme values of these experiments with 30 m-resolution are calculated from only 60 extreme values obtained from ASOS. On the other hand, the extreme value of EXP3 is similar to observation compared to others, since EXP3 produces 30m-resolution daily temperature through PRISM, and then applies GEV to that result at each grid point. This result indicates that the quality of statistically produced high-resolution extreme values which are estimated from observation data is different depending on the combination and procedure order of statistical methods.

• 한국항행학회논문지
• /
• 제16권5호
• /
• pp.846-852
• /
• 2012

영상분할 결과는 알고리즘에 관련된 매개변수들에 따라 다르기 때문에 최적 분할을 위하여 시행 착오법이 많이 이용된다. 본 논문에서는 3차원 변량 분석법을 이용하여 영역기반 active contour 방법에 관련된 최적 매개변수들을 결정하는 방법을 제안한다. 3원 변량 분석법에 의해서 추출된 결과와 사용자가 영상에서 직접 그린 결과가 상호 비교된다. 마지막으로 각 매개변수들의 주요 효과와 상호작용 효과를 측정하고 최적 값을 추출하기 위하여 점 추정 및 구간 추정 값을 계산한다. 본 논문에서 제안한 방법은 구간 상수 모델을 대상으로 영상분할시 최적 매개변수들을 추출하는데 큰 도움을 줄 것이다.

• 천문학회지
• /
• 제45권2호
• /
• pp.25-29
• /
• 2012

New methods are developed to estimate the effective temperature (Te), surface gravity (log g), and metallicity ([A/H]) simultaneously with the spectral line depth ratios. Using the model atmosphere grids, depth values are calculated for the wavelength range of $4000{\AA}-5600{\AA}$ for various temperatures, gravities, and metallicities. All possible different combinations of line depth ratios for different pairs of ratios are investigated. A graphical 3D figure is produced with X, Y, and Z axes corresponding to Te, log g, and [A/H], respectively. By reading a cross point of two curves plotted by a connection of three parameters obtained from spectral line depth ratio pairs on each of the three projected planes, Te, log g, and [A/H] are determined simultaneously. In addition, an analytical method is devised based on the similar algorithm developed for the graphical method. Our methods were applied to estimate the fundamental atmospheric parameters of the Sun and Arcturus.

• International Journal of CAD/CAM
• /
• 제5권1호
• /
• pp.19-27
• /
• 2005

As three-dimensional range scanners make large point clouds a more common initial representation of real world objects, a need arises for algorithms that can efficiently process point sets. In this paper, we present a method for extracting smooth surfaces from dense point clouds. Given an unorganized set of points in space as input, our algorithm first uses principal component analysis to estimate the surface variation at each point. After defining conditions for determining the geometric compatibility of a point and a surface, we examine the points in order of increasing surface variation to find points whose neighborhoods can be closely approximated by a single surface. These neighborhoods become seed regions for region growing. The region growing step clusters points that are geometrically compatible with the approximating surface and refines the surface as the region grows to obtain the best approximation of the largest number of points. When no more points can be added to a region, the algorithm stores the extracted surface. Our algorithm works quickly with little user interaction and requires a fraction of the memory needed for a standard mesh data structure. To demonstrate its usefulness, we show results on large point clouds acquired from real-world objects.