• Title, Summary, Keyword: Feature Expansion

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Three-dimensional Face Recognition based on Feature Points Compression and Expansion

  • Yoon, Andy Kyung-yong;Park, Ki-cheul;Park, Sang-min;Oh, Duck-kyo;Cho, Hye-young;Jang, Jung-hyuk;Son, Byounghee
    • Journal of Multimedia Information System
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    • v.6 no.2
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    • pp.91-98
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    • 2019
  • Many researchers have attempted to recognize three-dimensional faces using feature points extracted from two-dimensional facial photographs. However, due to the limit of flat photographs, it is very difficult to recognize faces rotated more than 15 degrees from original feature points extracted from the photographs. As such, it is difficult to create an algorithm to recognize faces in multiple angles. In this paper, it is proposed a new algorithm to recognize three-dimensional face recognition based on feature points extracted from a flat photograph. This method divides into six feature point vector zones on the face. Then, the vector value is compressed and expanded according to the rotation angle of the face to recognize the feature points of the face in a three-dimensional form. For this purpose, the average of the compressibility and the expansion rate of the face data of 100 persons by angle and face zone were obtained, and the face angle was estimated by calculating the distance between the middle of the forehead and the tail of the eye. As a result, very improved recognition performance was obtained at 30 degrees of rotated face angle.

A Semantic-Based Feature Expansion Approach for Improving the Effectiveness of Text Categorization by Using WordNet (문서범주화 성능 향상을 위한 의미기반 자질확장에 관한 연구)

  • Chung, Eun-Kyung
    • Journal of the Korean Society for information Management
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    • v.26 no.3
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    • pp.261-278
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    • 2009
  • Identifying optimal feature sets in Text Categorization(TC) is crucial in terms of improving the effectiveness. In this study, experiments on feature expansion were conducted using author provided keyword sets and article titles from typical scientific journal articles. The tool used for expanding feature sets is WordNet, a lexical database for English words. Given a data set and a lexical tool, this study presented that feature expansion with synonymous relationship was significantly effective on improving the results of TC. The experiment results pointed out that when expanding feature sets with synonyms using on classifier names, the effectiveness of TC was considerably improved regardless of word sense disambiguation.

A Study on Connected Digits Recognition Using the K-L Expansion (K-L 전개를 이용한 연속 숫자음 인식에 관한 연구)

  • 김주곤;오세진;황철준;김범국;정현열
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.3
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    • pp.24-31
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    • 2001
  • The K-L expansion is a method for compressing dimensions of features and thus reduces computational cost in recognition process. Also This is well known that features can be extracted without much loss of information in the statistical pattern recognition. In this paper, the method that effectively applies K-L(Karhunen-Loeve) expansion to feature parameters of speech is proposed to improve the recognition accuracy of the Korean speech recognition system. The recognition performance of a novel feature parameters obtained by the proposed method(K-L coefficients) is compared with those of conventional Mel-cepstrum and regressive coefficients through speaker independent connected digits recognition experiments. Experimental results showed that average recognition rates using the K-L coefficients with regression coefficients obtained higher accuracy than conventional Mel-cepstrum with their regression coefficients.

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Optimal Transmission Expansion Planning Considering the Uncertainties of Power Market (전력시장 불확실성을 고려한 최적 송전시스템 확장계획)

  • Son, Min-Kyun;Kim, Jin-O
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.4
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    • pp.560-566
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    • 2008
  • Today, as the power trades between generation companies and power customer are liberalized, the uncertainty level of operated power system is rapidly increased. Therefore, transmission operators as decision makers for transmission expansion are required to establish a deliberate investment plan for effective operations of transmission facilities considering forecasted conditions of power system. This paper proposes the methodology for the optimal solution of transmission expansion in deregulated power system. The paper obtains the expected value of transmission congestion cost for various scenarios by using occurrence probability. In addition, the paper assumes that increasing rates of loads are the probability distribution and indicates the location of expanded transmission line, the time for transmission expansion with the minimum cost for the future by performing the Montecarlo simulation. To minimize the investment risk as the variance of the congestion cost, Mean-Variance Markowitz portfolio theory is applied to the optimization model by the penalty factor of the variance. By the case study, the optimal solution for transmission expansion plan considering the feature of market participants is obtained.

Image Comparison Using Directional Expansion Operation

  • Yoo, Suk Won
    • International Journal of Advanced Culture Technology
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    • v.6 no.3
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    • pp.173-177
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    • 2018
  • Masks are generated by adding different fonts of learning data characters in pixel unit, and pixel values belonging to each of the masks are divided into 3 groups. Using the directional expansion operators, we expand the text area of the test data character into 4 diagonal directions in order to create the boundary areas to distinguish it from the background area. A mask with a minimum average discordance is selected as the final recognition result by calculating the degree of discordance between the expanded test data and the masks. Image comparison using directional expansion operations more accurately recognizes test data through 4 subdivided recognition processes. It is also possible to expand the ranges of 3 groups of pixel values of masks more evenly such that new fonts can easily be added to the given learning data.

Optical Flow for Motion Images with Large Displacement by Functional Expansion

  • Kim, Jin-Woo
    • Journal of Korea Multimedia Society
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    • v.7 no.12
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    • pp.1680-1691
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    • 2004
  • One of the representative methods of optical flow is a gradient method which estimates the movement of an object based on the differential of image brightness. However, the method is ineffective for large displacement of the object and many improved methods have been proposed to copy with such limitations. One of these improved techniques is the multigrid processing, which is used in many optical flow algorithms. As an alternative novel technique we have been proposing an orthogonal functional expansion method, where whole displacements are expanded from low frequency terms. This method is expected to be applicable to flow estimation with large displacement and deformation including expansion and contraction, which are difficult to cope with by conventional optical flow methods. In the orthogonal functional expansion method, the apparent displacement field is calculated iteratively by a projection method which utilizes derivatives of the invariant constraint equations of brightness constancy. One feature of this method is that differentiation of the input image is not necessary, thereby reducing sensitivity to noise. In this paper, we apply our method to several real images in which the objects undergo large displacement and/or deformation including expansion. We demonstrate the effectiveness of the orthogonal functional expansion method by comparing with conventional methods including our optimally scaled multigrid optical flow algorithm.

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Model-independent constraints on the light-curve parameters and reconstructions of the expansion history from Type Ia supernovae

  • Koo, Hanwool;Shafieloo, Arman;Keeley, Ryan;L'Huillier, Benjamin
    • The Bulletin of The Korean Astronomical Society
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    • v.44 no.2
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    • pp.54.1-54.1
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    • 2019
  • We use iterative smoothing reconstruction method along with exploring in the parameter space of the light curves of the JLA supernova compilation (Joint Light-curve Analysis) to simultaneously reconstruct the expansion history of the universe as well as putting constrains on the light curve parameters without assuming any cosmological model. Our constraints on the light curve parameters of the JLA from our model-independent analysis seems to be closely in agreement with results assuming ΛCDM cosmology or using Chevallier-Polarski-Linder (CPL) parametrization for the equation of state of dark energy. This implies that there is no hidden significant feature in the data that could be neglected by cosmology model assumption. The reconstructed expansion history of the universe and properties of dark energy seems to be in good agreement with expectations of the standard ΛCDM model. Our results also indicate that the data allows a considerable flexibility for expansion history of the universe.

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Syllable Recognition of HMM using Segment Dimension Compression (세그먼트 차원압축을 이용한 HMM의 음절인식)

  • Kim, Joo-Sung;Lee, Yang-Woo;Hur, Kang-In;Ahn, Jum-Young
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.2
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    • pp.40-48
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    • 1996
  • In this paper, a 40 dimensional segment vector with 4 frame and 7 frame width in every monosyllable interval was compressed into a 10, 14, 20 dimensional vector using K-L expansion and neural networks, and these was used to speech recognition feature parameter for CHMM. And we also compared them with CHMM added as feature parameter to the discrete duration time, the regression coefficients and the mixture distribution. In recognition test at 100 monosyllable, recognition rates of CHMM +${\bigtriangleup}$MCEP, CHMM +MIX and CHMM +DD respectively improve 1.4%, 2.36% and 2.78% over 85.19% of CHMM. And those using vector compressed by K-L expansion are less than MCEP + ${\bigtriangleup}$MCEP but those using K-L + MCEP, K-L + ${\bigtriangleup}$MCEP are almost same. Neural networks reflect more the speech dynamic variety than K-L expansion because they use the sigmoid function for the non-linear transform. Recognition rates using vector compressed by neural networks are higher than those using of K-L expansion and other methods.

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The Expression of Fashion Design Using a Maximalism Character (맥시멀리즘 특징을 이용한 패션디자인의 표현성 연구)

  • Kim, Hyun-Jin;Lee, Eun-Sook
    • Fashion & Textile Research Journal
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    • v.13 no.1
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    • pp.7-16
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    • 2011
  • Maximalism is the code which has a power to interpret a fashion phenomenon expressed complexly and variously in the multicultural society. In the 21st century, maximalism which reappeared is not the expression by a method only. It is presenting the experimental design for the new pursuit through the mixture such as expansion, splendor, variety, decoration, distortion of configuration or transformation, and composition. Therefore, this study aims at analyzing expression of fashion design by four types(expansion, decoration, mixture, non-structure) materializing a feature of maximalism expressed in the domestic and foreign collection works from 2005 to 2010. The research results are as follows. 1. Expansion: It was showed artificial, formative, unique, and odd teatures through the expansion of the upper half of the body, the lower half of the body, and both of them. 2. Decoration: It was showed the actual decoration considering functionality and practicality and the decoration emphasizing and unique character and featuring domination and emphasis. 3. Mixture: It was showed through the mixture of the contrary textiles or the different sex image. 4. Non-structure: It showed the non-structure of the avant-garde trend and non-structure through decoration, detail, adjustment direction of a dress.

Enhancement of Internal Control by expanding Security Information Event Management System

  • Im, DongSung;Kim, Yongmin
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.8
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    • pp.35-43
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    • 2015
  • Recently, internal information leaks is increasing rapidly by internal employees and authorized outsourcing personnel. In this paper, we propose a method to integrate internal control systems like system access control system and Digital Rights Managements and so on through expansion model of SIEM(Security Information Event Management system). this model performs a analysis step of security event link type and validation process. It develops unit scenarios to react illegal acts for personal information processing system and acts to bypass the internal security system through 5W1H view. It has a feature that derives systematic integration scenarios by integrating unit scenarios. we integrated internal control systems like access control system and Digital Rights Managements and so on through expansion model of Security Information Event Management system to defend leakage of internal information and customer information. We compared existing defense system with the case of the expansion model construction. It shows that expanding SIEM was more effectively.