• Title/Summary/Keyword: Feature Parameter

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Camera Extrinsic Parameter Estimation using 2D Homography and LM Method based on PPIV Recognition (PPIV 인식기반 2D 호모그래피와 LM방법을 이용한 카메라 외부인수 산출)

  • Cha Jeong-Hee;Jeon Young-Min
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.43 no.2 s.308
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    • pp.11-19
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    • 2006
  • In this paper, we propose a method to estimate camera extrinsic parameter based on projective and permutation invariance point features. Because feature informations in previous research is variant to c.:men viewpoint, extraction of correspondent point is difficult. Therefore, in this paper, we propose the extracting method of invariant point features, and new matching method using similarity evaluation function and Graham search method for reducing time complexity and finding correspondent points accurately. In the calculation of camera extrinsic parameter stage, we also propose two-stage motion parameter estimation method for enhancing convergent degree of LM algorithm. In the experiment, we compare and analyse the proposed method with existing method by using various indoor images to demonstrate the superiority of the proposed algorithms.

Extraction and Implementation of MPEG-4 Facial Animation Parameter for Web Application (웹 응용을 위한 MPEC-4 얼굴 애니메이션 파라미터 추출 및 구현)

  • 박경숙;허영남;김응곤
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.8
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    • pp.1310-1318
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    • 2002
  • In this study, we developed a 3D facial modeler and animator that will not use the existing method by 3D scanner or camera. Without expensive image-input equipments, we can easily create 3D models only using front and side images. The system is available to animate 3D facial models as we connect to animation server on the WWW which is independent from specific platforms and softwares. It was implemented using Java 3D API. The facial modeler detects MPEG-4 FDP(Facial Definition Parameter) feature points from 2D input images, creates 3D facial model modifying generic facial model with the points. The animator animates and renders the 3D facial model according to MPEG-4 FAP(Facial Animation Parameter). This system can be used for generating an avatar on WWW.

A Large-scale Structural Mixing Model applied to Blowout of Turbulent Nonpremixed Jet Flames in a Cross air-flow

  • Lee, Kee-Man;Shin, Hyun-Dong
    • 한국연소학회:학술대회논문집
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    • 1997.06a
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    • pp.163-173
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    • 1997
  • This article presents an application of a large-scale structural mixing model (Broadwell et al. 1984) to the blowout of turbulent reacting jets discharging perpendicularly into an unconfined cross air-flow. In an analysis of a common stability curve, a plausible explanation can be made that the phenomenon of blowout is related only to the mixing time scale of the two flows. The most notable observation is that the blowout distance is traced at fixed positions at all times according to the velocity ratio R. Measurements of the lower blowout limits in the liftable flame agree qualitatively with the blowout parameter ${\varepsilon}$, proposed by Broadwell et al. Good agreement between the results calculated by a modified blowout parameter ${\varepsilon}^'$ and experimental results confirms the important effect of a large-scale structure in specifying the stabilization feature of blowouts.

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Identification of Friction Condition with Neural Network (신경회로망에 의한 마찰상태의 식별)

  • 조연상;서영백;박흥식;전태옥
    • Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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    • 1998.04a
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    • pp.83-90
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    • 1998
  • The morphologies of the wear debris are directly indicative of wear processes occuring in machinery and their severity. The neural network was applied to identify friction condition from the lubricated moving system. The four parameter(50% volumetric diameter, aspect, roundness and reflectivity) of wear debris are used as inputs to the network and learned the friction coefficient. It is shown that identification results depend on the ranges of these shape parameter learned. The three kinds of the wear debris had a different pattern characteristic and recognized the friction condition and materials very well by neural network. We dicuss between the characteristic of wear debris and the friction coefficient and how the network determines difference in wear debris feature.

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Robust Entropy Based Voice Activity Detection Using Parameter Reconstruction in Noisy Environment

  • Han, Hag-Yong;Lee, Kwang-Seok;Koh, Si-Young;Hur, Kang-In
    • Journal of information and communication convergence engineering
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    • v.1 no.4
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    • pp.205-208
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    • 2003
  • Voice activity detection is a important problem in the speech recognition and speech communication. This paper introduces new feature parameter which are reconstructed by spectral entropy of information theory for robust voice activity detection in the noise environment, then analyzes and compares it with energy method of voice activity detection and performance. In experiments, we confirmed that spectral entropy and its reconstructed parameter are superior than the energy method for robust voice activity detection in the various noise environment.

A REVERSIBLE IMAGE AUTHENTICATION METHOD FREE FROM LOCATION MAP AND PARAMETER MEMORIZATION

  • Han, Seung-Wu;Fujiyoshi, Masaaki;Kiya, Hitoshi
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2009.01a
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    • pp.572-577
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    • 2009
  • This paper proposes a novel reversible image authentication method that requires neither location map nor memorization of parameters. The proposed method detects image tampering and further localizes tampered regions. Though this method once distorts an image to hide data for tamper detection, it recovers the original image from the distorted image unless no tamper is applied to the image. The method extracts hidden data and recovers the original image without memorization of any location map that indicates hiding places and of any parameter used in the algorithm. This feature makes the proposed method practical. Simulation results show the effectiveness of the proposed method.

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Parameter Identification of an Induction Motor Drive with Magnetic Saturation for Electric Vehicle

  • Jeong, Yu-Seok;Lee, Jun-Young
    • Journal of Power Electronics
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    • v.11 no.4
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    • pp.418-423
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    • 2011
  • This paper presents a simulation model and a parameter identification scheme of an induction motor drive for electric vehicle. The induction motor in automotive applications should operate in very high efficiency and achieve the maximum-torque-per-ampere (MTPA) feature even with saturated magnetic flux under very high torque. The indirect vector control which is typically adopted in traction drive system requires precise information of motor parameters, particularly rotor time constants. This work models an induction motor considering magnetic saturation and proposes an empirical identification method using the current controller in the synchronous reference frame. The proposed method is applied to a 22kW-rated induction motor for electric vehicle.

Surface Type Detection and Parameter Estimation in Point Cloud by Using Orthogonal Distance Fitting (최단거리 최소제곱법을 이용한 측정점군으로부터의 곡면 자동탐색)

  • Ahn, Sung-Joon
    • Korean Journal of Computational Design and Engineering
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    • v.14 no.1
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    • pp.10-17
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    • 2009
  • Surface detection and parameter estimation in point cloud is a relevant subject in CAD/CAM, reverse engineering, computer vision, coordinate metrology and digital factory. In this paper we present a software for a fully automatic surface detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting, which work interactively. Our newly developed algorithms for orthogonal distance fitting(ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. We demonstrate the performance of the software on a variety of point clouds generated by laser radar, computer tomography, and stripe-projection method.

Automatic Determination of Constraint Parameter for Improving Homography Matrix Calculation in RANSAC Algorithm

  • Chandra, Devy;Lee, Kee-Sung;Jo, Geun-Sik
    • Proceedings of the Korea Information Processing Society Conference
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    • 2014.04a
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    • pp.830-833
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    • 2014
  • This paper proposes dynamic constraint parameter to filter out degenerate configurations (i.e. set of collinear or adjacent features) in RANSAC algorithm. We define five different groups of image based on the feature distribution pattern. We apply the same linear and distance constraints for every image, but we use different constraint parameter for every group, which will affect the filtering result. An evaluation is done by comparing the proposed dynamic CS-RANSAC algorithm with the classic RANSAC and regular CS-RANSAC algorithms in the calculation of a homography matrix. The experimental results show that dynamic CS-RANSAC algorithm provides the lowest error rate compared to the other two algorithms.

Locating and Extracing the Mouth in Human Face Images (얼굴 이미지에서 입 영역 분할)

  • Choe, Jeong-Il;Kim, Su-Hwan;Lee, Pil-Gyu
    • Korean Journal of Cognitive Science
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    • v.8 no.4
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    • pp.55-62
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    • 1997
  • We proposed a method for locating of mouth using deformable templates, described by a parameterized template. An energy function is defined which links, edges, peaks, valleys in image intensity to corresponding properties of the template. The template deforms itself by altering its parameter values to minimize the energy function. The minimized energy function's parameter values can be used as descriptors for the feature. We propose a method for locating mouth fast, accurately by limiting a range of parameters' value and getting initial value of parameters' by preprocessing.

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