• 제목/요약/키워드: Feature Parameter

검색결과 533건 처리시간 0.025초

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

  • 차정희;전영민
    • 전자공학회논문지SC
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    • 제43권2호
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    • pp.11-19
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    • 2006
  • 본 논문에서는 사영과 치환불변 점 특징을 기반으로 카메라의 외부인수를 산출하는 방법을 제안한다. 기존 연구에서의 특징 정보들은 카메라의 뷰 포인트에 따라 변화하기 때문에 대응점 산출이 어렵다. 따라서 본 논문에서는 카메라 위치에 무관한 불변 점 특징을 추출하고 시간 복잡도 감소와 정확한 대응점 산출을 위해 유사도 평가함수와 Graham 탐색 방법을 이용한 새로운 정합방법을 제안한다. 또한 카메라 외부인수 산출단계에서는 LM 알고리즘의 수렴도를 향상시키기 위해 2단계 카메라 동작인수 산출방법을 제안한다. 실험에서는 다양한 실내영상을 이용하여 기존방법과 비교, 분석함으로써 제안한 알고리즘의 우수성을 입증하였다.

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

  • 박경숙;허영남;김응곤
    • 한국정보통신학회논문지
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    • 제6권8호
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    • pp.1310-1318
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    • 2002
  • 본 연구에서는 기존의 방법에 비하여 값비싼 3차원 스캐너나 카메라를 이용하지 않고 정면과 측면 영상을 이용하여 3차원 모델을 생성하는 3차원 얼굴 모델러와 애니메이터를 개발하였다. 이 시스템은 특정한 플랫폼과 소프트웨어에 독립적으로 웹상에서 애니메이션 서버에 접속함으로써 3차원 얼굴 모델을 애니메이션 할 수 있으며 자바 3D API를 이용하여 구현하였다. 얼굴모델러는 입력 영상으로부터 MPEG-4 FDP(Facial Definition Parameter) 특징점을 추출하여 일반 얼굴모델을 특징점에 따라 변형시켜 3차원 얼굴 모델을 생성한다 애니메이터는 FAP(Facial Animation Parameter)에 따라 얼굴모델을 애니메이션하고 렌더링한다. 본 시스템은 웹 상에서 아바타를 제작하는 데 사용될 수 있다.

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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    • 한국연소학회 1997년도 제15회 KOSCO SYMPOSIUM 논문집
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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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신경회로망에 의한 마찰상태의 식별 (Identification of Friction Condition with Neural Network)

  • 조연상;서영백;박흥식;전태옥
    • 한국윤활학회:학술대회논문집
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    • 한국윤활학회 1998년도 제27회 춘계학술대회
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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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    • 제1권4호
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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
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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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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    • 제11권4호
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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.

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

  • 안성준
    • 한국CDE학회논문집
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    • 제14권1호
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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
    • 한국정보처리학회:학술대회논문집
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    • 한국정보처리학회 2014년도 춘계학술발표대회
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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.

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

  • 최정일;김수환;이필규
    • 인지과학
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    • 제8권4호
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    • pp.55-62
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    • 1997
  • 본 논문은 매개변수 템플리트로 알려진 가변 형판(deformable template)을 사용하여 얼굴의 주요 구성 요소인 입 영역을 분할하는 방법을 제안한다. 가변 형판의 에너지 함수는 이미지 명암값(intensity), 연결(links), 에지(edges), 피크(peaks), 밸리(valleys) 등의 식으로 정의된다. 이 템플리트는 에너지 함수를 최소화하도록 매개변수들의 값을 변경함으로써 자신을 최적화하면서 변형된다. 이 최적화된 템플리트의 매개변수들의 값은 특징으로 사용된다. 우리는 이 가변 형판의 매개변수들의 초기값과 범위를 전처리를 통하여 구하여 시행시간을 줄이고 정확한 입 영역을 분할하는 방법을 제안한다.

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