• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2005.04a
• /
• pp.273-276
• /
• 2005

본 논문은 고유얼굴 방법을 이용한 얼굴인식 시스템의 성능을 분석하였다. 제안한 고유얼굴을 이용한 얼굴인식 방법은 훈련집합의 얼굴 이미지 사이의 중요한 변화를 가지고 있는 특징공간으로 투영시키면서 이루어진다. 중요한 특징들은 얼굴집합의 고유벡터(주성분)들이기 때문에 고유얼굴이라 한다. 특징 공간으로의 투영은 고유얼굴의 가중치의 합으로 입력얼굴을 기술할 수 있으며, 입력 얼굴의 인식은 훈련집합의 가중치와 입력 영상의 가중치를 비교하면서 이루어진다. 본 논문에서는 제안된 방법의 검증을 위해서 Harvard 데이터베이스를 이용하였으며, 시스템의 성능 분석을 위하여 조명에 대한 인식성능의 변화, 사용한 고유얼굴의 수에 대한 인식률의 변화, 전처리를 통하여 얻을 수 있는 인식률의 변화, 인식 거부 곡선을 통하여 시스템의 적용 가능성에 대한 실험을 수행하여 분석한다.

• Journal of Korean Society for Geospatial Information Science
• /
• v.5 no.2 s.10
• /
• pp.65-75
• /
• 1997

Nowadays, digital map plays a role as a container of spatial database.'there have been many researches concerning the improvements of the digital map accuracy. From the user's viewpoint, however, the quality level of digital nap is as important as its accuracy, because fitness-for-use is considered the most important factor to the users. This study aims to find the methodology for determining the grade nか digital map. To accomplish this, we propose two major stages. First, weight factors of the layers are given according to the importance of the functions which must be considered in digital map generation. Scond, weight factors of the components to evaluate the accuracy of the digital map are presented By scoring the components and by summing the scores, the method for determining fitness-for-use is developed.

• Journal of KIISE:Databases
• /
• v.32 no.3
• /
• pp.228-242
• /
• 2005

The projected clustering seeks to find clusters in different subspaces within a high dimensional dataset. We propose an algorithm to discover near optimal projected clusters without user specified parameters such as the number of output clusters and the average cardinality of subspaces of projected clusters. The objective function of the algorithm computes projected energy, quality, and the number of outliers in each process of clustering. In order to minimize the projected energy and to maximize the quality in clustering, we start to find best subspace of each cluster on the density of input points by comparing standard deviations of the full dimension. The weighting factor for each dimension of the subspace is used to get id of probable error in measuring projected distances. Our extensive experiments show that our algorithm discovers projected clusters accurately and it is scalable to large volume of data sets.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.198-201
• /
• 2009

In this paper, an eye tracking method is presented by using on iterated spatial moment adapting weighted gray level that can accurately detect and track user's eyes under the complicated background. The region of face is detected by using Haar-like feature before extracting region of eyes to minimize an region of interest from the input picture of CCD camera. And the region of eyes is detected by using eigeneye based on the eigenface of Principal component analysis. And then feature points of eyes are detected from darkest part in the region of eyes. The tracking of eyes is achieved correctly by using iterated spatial moment adapting weighted gray level.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.11a
• /
• pp.104-107
• /
• 2007

인간은 초점정보를 이용하여 단안만으로도 공간의 깊이를 지각할 수 있다. 이것은 한 번에 하나의 대상물에만 초점을 맞출 수 있고 그 외의 부분은 흐림 현상을 유도함으로써 이루어진다. 이는 초점이 맞는 대상물체로부터 멀어지면 멀어질수록 흐림 현상이 강해지는 원리를 이용한 것으로 주파수 성분의 변화량에 대한 연산과 깊은 관련이 있다. 본 논문에서는 이와 같은 인간의 시각 시스템의 요소 중 하나인 초점정보를 모방하여 초점거리가 다른 각각의 이미지들에 각각의 가중치를 부여하였다. 그리고 각 이미지들을 일정 블록으로 각각 분할하여 초점이 가장 잘 맞는 블록을 찾아내어 하나의 이미지로 통합하였다. 이때 각 영역은 자신이 속했던 이미지의 가중치를 따르게 한다. 각 이미지에서 가장 포커스 수치가 높은 영역을 찾기 위한 방법으로 주파수 영역 기반 처리와 공간 영역 기반 처리를 결합 하였다. 주파수 기반으로는 FFT(Fast Fourier Transform)에서 고주파 부분의 영역을 뽑아내어 포커스수치를 계산하였으며, 공간 영역 처리 기반으로는 이웃픽셀과의 차이가 임계값이하인 것을 제외한 영역을 뽑아내어 저주파 영역의 연산을 제거하는 방법과 단순히 Laplacian measure만을 사용하여 저주파까지도 포함한 방법의 두 가지를 적용하였다. 최종적으로 3개의 포커스 측정값을 결합시켜 포커스 수치를 계산한 후 각 블록의 가중치에 맞게 하나의 이미지로 통합하여 상대적 깊이지도를 생성하였다.

• The KIPS Transactions:PartA
• /
• v.13A no.3 s.100
• /
• pp.267-274
• /
• 2006

This paper describes a method to achieve different level of detail for the given volumetric data by assigning weight for the given data points. The relation between wavelet transformation and alpha shape was investigated to define the different level of resolution. Scattered data are defined as a collection of data that have little specified connectivity between data points. The quality of interpolant in volumetric trivariate space depends not only on the distribution of the data points in ${\Re}^3$, but also on the data value (intensity). We can improve the quality of an approximation by using wavelet coefficient as weight for the corresponding data points.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2022.01a
• /
• pp.163-164
• /
• 2022

본 연구는 최근 2년(2019.12.1.~2021. 11.30)간 빅카인즈를 이용하여 '메타버스 AND 비대면 교육' 키워드가 포함된 뉴스 검색 결과 1148건을 바탕으로 관계도 분석, 연관어 키워드 빈도수 및 연관어 가중치 분석을 하였다. 첫째, 관계도 분석에서 가중치 '5'로 적용한 12개의 키워드 가중치로 코로나19(64), 아바타(43), 코로나(22), 유니버스(21), 게더타운(15), 패러다임(12), 신입사원(12), 로블록스(7)로 나타났다. 둘째, 연관어 키워드 월간 빈도수로는 2019.12~ 2020.9(0건), 2020.10(1건), 2021.3(19건), 2021.4(34건), 2021.6(72건), 2021.9 (196건), 2021.11애는 233건으로 급격하게 증가하였다. 셋째 키워드와의 연관성(가중치/키워드 빈도수)으로 코로나19(113.96/515), 가상세계(67.75/ 344), 메타버스(58.36/103), 메타(49.8/5730), 가상공간(45.57/380) 순이었다. 이 분석 결과에서 위드코로나 시대의 비대면 교육으로 메타버스에 기반을 둔 가상공간 활용 교육은 더욱 증가될 것으로 예상된다.

• The Transactions of the Korea Information Processing Society
• /
• v.4 no.6
• /
• pp.1418-1432
• /
• 1997

Most general content_based image retrieval techniques use color and texture as retrieval indices. In color techniques, color histogram and color pair based color retrieval techniques suffer from a lack of spatial information and text. And This paper describes the design and implementation of content_based image retrieval system using color space and keywords. The preprocessor for image retrieval has used the coordinate system of the existing HSI(Hue, Saturation, Intensity) and preformed to split One image into chromatic region and achromatic region respectively, It is necessary to normalize the size of image for 200*N or N*200 and to convert true colors into 256 color. Two color histograms for background and object are used in order to decide on color selection in the color space. Spatial information is obtained using a maximum entropy discretization. It is possible to choose the class, color, shape, location and size of image by using keyword. An input color is limited by 15 kinds keyword of chromatic and achromatic colors of the Korea Industrial Standards. Image retrieval method is used as the key of retrieval properties in the similarity. The weight values of color space ${\alpha}(%)and\;keyword\;{\beta}(%)$ can be chosen by the user in inputting the query words, controlling the values according to the properties of image_contents. The result of retrieval in the test using extracted feature such as color space and keyword to the query image are lower that those of weight value. In the case of weight value, the average of te measuring parameters shows approximate Precision(0.858), Recall(0.936), RT(1), MT(0). The above results have proved higher retrieval effects than the content_based image retrieval by using color space of keywords.

• Journal of Broadcast Engineering
• /
• v.18 no.3
• /
• pp.455-462
• /
• 2013

This paper introduces the Spatially Preprocessed Speech Distortion Weighted Multi-channel Wiener Filter (SP-SDW-MWF) for multi-microphone noise reduction and proposes a method to determine the speech distortion weights. The SP-SDW-MWF is known as a robust noise reduction algorithm against the error caused by the mismatch in microphones. The SP-SDW-MWF adopts weights which determine the amount of noise reduction at the expense of introducing speech distortion in the noise-suppressed speech. In this paper, we use the error of power spectral density between the estimated signal and the desired signal as the evaluation measure. Thus the a priori SNR is used to control the speech distortion weights in the frequency domain. In the experimental results, the proposed method yields better result in terms of MFCC distortion compared to the conventional method.

• Communications for Statistical Applications and Methods
• /
• v.17 no.2
• /
• pp.193-204
• /
• 2010

Recently, researchers of the various fields where the spatial analysis is needed have more interested in spatial statistics. In case of data with spatial correlation, methodologies accounting for the correlation are required and there have been developments in methods for spatial data analysis. Lattice data among spatial data is analyzed with following three procedures: (1) definition of the spatial neighborhood, (2) definition of spatial weight, and (3) the analysis using spatial models. The present paper shows a spatial statistical analysis method superior to a general statistical method in aspect estimation by using the trimmed mean squared error statistic, when we analysis the spatial lattice data that outliers are included. To show validation and usefulness of contents in this paper, we perform a small simulation study and show an empirical example with a criminal data in BusanJin-Gu, Korea.