• Title/Summary/Keyword: 2D 호모그래피

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CSP driven RANSAC Algorithm for improving the accuracy of Homography (호모그래피 정확도 향상을 위한 Constraint Satisfaction Problem(CSP) 기반의 RANSAC 알고리즘)

  • Jang, Chol-Hee;Lee, Kee-Sung;Jo, Geun-Sik
    • Proceedings of the Korean Information Science Society Conference
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    • 2012.06b
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    • pp.318-320
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    • 2012
  • 증강현실 콘텐츠를 2D 이미지기반으로 저작할 때, 작성된 증강현실 콘텐츠를 카메라 시점과 일치시켜 합성하기 위해 호모그래피를 이용한다. 이때 증강현실 콘텐츠를 이질감 없이 합성하기위해 정확한 호모그래피 행렬을 추정해야 한다. 그러나 호모그래피 행렬 추정 시 사용되는 특징점들이 선형을 이루거나, 특정 영역에 군집을 이루는 경우 정확한 호모그래피 행렬을 추정하지 못하는 문제가 발생한다. 본 논문에서는 이러한 문제를 해결하기 위해 선형제약, 거리제약을 적용한 CSP 기반의 RANSAC 알고리즘을 제안한다. 실험결과 호모그래피 행렬 추정 시 CSP를 적용한 RANSAC 알고리즘이 기존의 랜덤샘플링 또는 삼각형의 넓이를 이용한 샘플링을 적용한 RANSAC 알고리즘보다 정확도가 향상됨을 보였다.

Multiple Homographies Estimation using a Guided Sequential RANSAC (가이드된 순차 RANSAC에 의한 다중 호모그래피 추정)

  • Park, Yong-Hee;Kwon, Oh-Seok
    • The Journal of the Korea Contents Association
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    • v.10 no.7
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    • pp.10-22
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    • 2010
  • This study proposes a new method of multiple homographies estimation between two images. With a large proportion of outliers, RANSAC is a general and very successful robust parameter estimator. However it is limited by the assumption that a single model acounts for all of the data inliers. Therefore, it has been suggested to sequentially apply RANSAC to estimate multiple 2D projective transformations. In this case, because outliers stay in the correspondence data set through the estimation process sequentially, it tends to progress slowly for all models. And, it is difficult to parallelize the sequential process due to the estimation order by the number of inliers for each model. We introduce a guided sequential RANSAC algorithm, using the local model instances that have been obtained from RANSAC procedure, which is able to reduce the number of random samples and deal simultaneously with multiple models.

A Study on registration using homography for 3D modeling (호모그래피를 이용한 3D 모델링을 위한 데이터 정합에 관한 연구)

  • Kim, Sang-Hoon
    • Journal of Digital Contents Society
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    • v.15 no.4
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    • pp.521-526
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    • 2014
  • The purpose of this study is to propose the efficient method of 3D data registration. Three-dimensional data including the two-dimensional image acquisition apparatus and the position information are acquired at an arbitrary angle with each other. This paper proposes the more accurate and faster matching method by using this information. Four image points founded from 2D images match the volumetric size of the model and compute the homography of the axis for registration between two 3D data sets. The advantages of the proposed algorithm are the repeating process is unnecessary and the process time is faster than prvious method.

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.

Virtual Two-View Technique for Real 3D Hand Interface (사실적 3D 손 인터페이스를 위한 가상 양시점화 기법)

  • Bae, Dong-Hee;Kim, Jin-Mo;Cho, Hyung-Je
    • Proceedings of the Korean Information Science Society Conference
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    • 2010.06b
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    • pp.162-166
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    • 2010
  • 기존의 인간과 컴퓨터 사이의 상호작용을 제어하는 손 인터페이스들은 대부분이 2차원 영상을 분석, 제어하는 간단한 구조로 되어 있거나 3차원 분석의 경우 주로 두 대의 카메라로 영상을 입력 받아 매 프레임 많은 연산을 처리하는 불필요한 구조로 구현된 경우가 많다. 본 논문에서 제안하는 가상 양시점화 기법은 두 카메라 사이의 변환 정보를 호모그래피(Homography) 행렬로 계산한 후에는 오직 한 대의 카메라만을 이용하여 사실적인 3차원 손 좌표 복원을 수행한다. 즉, 초기에 구해진 호모그래피 행렬을 통해 가상의 두 번째 카메라의 좌표 값을 예측하여 한 대의 카메라만을 사용하면서도 두 대의 카메라로 처리하는 것과 같은 결과를 얻으려는 시도이다. 이는 단일 손 영상을 분석하여 3차원 정보를 유추하는 기존의 3차원 손인터페이스 방식에 비해 보다 정확한 3차원 정보를 얻을 수 있으며, 두 대의 카메라를 동시에 구동할 때보다 연산량의 감소로 실시간 처리에 있어 효율적이다.

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Vision based 3D Hand Interface Using Virtual Two-View Method (가상 양시점화 방법을 이용한 비전기반 3차원 손 인터페이스)

  • Bae, Dong-Hee;Kim, Jin-Mo
    • Journal of Korea Game Society
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    • v.13 no.5
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    • pp.43-54
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    • 2013
  • With the consistent development of the 3D application technique, visuals are available at more realistic quality and are utilized in many applications like game. In particular, interacting with 3D objects in virtual environments, 3D graphics have led to a substantial development in the augmented reality. This study proposes a 3D user interface to control objects in 3D space through virtual two-view method using only one camera. To do so, homography matrix including transformation information between arbitrary two positions of camera is calculated and 3D coordinates are reconstructed by employing the 2D hand coordinates derived from the single camera, homography matrix and projection matrix of camera. This method will result in more accurate and quick 3D information. This approach may be advantageous with respect to the reduced amount of calculation needed for using one camera rather than two and may be effective at the same time for real-time processes while it is economically efficient.

Camera Extrinsic Parameter Estimation using 2D Homography and Nonlinear Minimizing Method based on Geometric Invariance Vector (기하학적 불변벡터 기탄 2D 호모그래피와 비선형 최소화기법을 이용한 카메라 외부인수 측정)

  • Cha, Jeong-Hee
    • Journal of Internet Computing and Services
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    • v.6 no.6
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    • pp.187-197
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    • 2005
  • In this paper, we propose a method to estimate camera motion parameter based on invariant point features, Typically, feature information of image has drawbacks, it is variable to camera viewpoint, and therefore information quantity increases after time, The LM(Levenberg-Marquardt) method using nonlinear minimum square evaluation for camera extrinsic parameter estimation also has a weak point, which has different iteration number for approaching the minimal point according to the initial values and convergence time increases if the process run into a local minimum, In order to complement these shortfalls, we, first proposed constructing feature models using invariant vector of geometry, Secondly, we proposed a two-stage calculation method to improve accuracy and convergence by using 2D homography and LM method, In the experiment, we compared and analyzed the proposed method with existing method to demonstrate the superiority of the proposed algorithms.

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Estimation of Camera Motion Parameter using Invariant Feature Models (불변 특징모델을 이용한 카메라 동작인수 측정)

  • Cha, Jeong-Hee;Lee, Keun-Soo
    • Journal of the Korea Society of Computer and Information
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    • v.10 no.4 s.36
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    • pp.191-201
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    • 2005
  • In this paper, we propose a method to calculate camera motion parameter, which is based on efficient invariant features irrelevant to the camera veiwpoint. As feature information in previous research is variant to camera viewpoint. information content is increased, therefore, extraction of accurate features is difficult. LM(Levenberg-Marquardt) method for camera extrinsic parameter converges on the goat value exactly, but it has also drawback to take long time because of minimization process by small step size. Therefore, in this paper, we propose the extracting method of invariant features to camera viewpoint and two-stage calculation method of camera motion parameter which enhances accuracy and convergent degree by using camera motion parameter by 2D homography to the initial value of LM method. The proposed method are composed of features extraction stage, matching stage and calculation stage of motion parameter. In the experiments, we compare and analyse the proposed method with existing methods by using various indoor images to demonstrate the superiority of the proposed algorithm.

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3-D Pose Estimation of an Elliptic Object Using Two Coplanar Points (두 개의 공면점을 활용한 타원물체의 3차원 위치 및 자세 추정)

  • Kim, Heon-Hui;Park, Kwang-Hyun;Ha, Yun-Su
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.49 no.4
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    • pp.23-35
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    • 2012
  • This paper presents a 3-D pose (position and orientation) estimation method for an elliptic object in 3-D space. It is difficult to resolve the problem of determining 3-D pose parameters with respect to an elliptic feature in 3-D space by interpretation of its projected feature onto an image plane. As an alternative, we propose a two points-based pose estimation algorithm to seek the 3-D information of an elliptic feature. The proposed algorithm determines a homogeneous transformation uniquely for a given correspondence set of an ellipse and two coplanar points that are defined on model and image plane, respectively. For each plane, two triangular features are extracted from an ellipse and two points based on the polarity in 2-D projection space. A planar homography is first estimated by the triangular feature correspondences, then decomposed into 3-D pose parameters. The proposed method is evaluated through a series of experiments for analyzing the errors of 3-D pose estimation and the sensitivity with respect to point locations.

Detection of the co-planar feature points in the three dimensional space (3차원 공간에서 동일 평면 상에 존재하는 특징점 검출 기법)

  • Seok-Han Lee
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.16 no.6
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    • pp.499-508
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    • 2023
  • In this paper, we propose a technique to estimate the coordinates of feature points existing on a 2D planar object in the three dimensional space. The proposed method detects multiple 3D features from the image, and excludes those which are not located on the plane. The proposed technique estimates the planar homography between the planar object in the 3D space and the camera image plane, and computes back-projection error of each feature point on the planar object. Then any feature points which have large error is considered as off-plane points and are excluded from the feature estimation phase. The proposed method is archived on the basis of the planar homography without any additional sensors or optimization algorithms. In the expretiments, it was confirmed that the speed of the proposed method is more than 40 frames per second. In addition, compared to the RGB-D camera, there was no significant difference in processing speed, and it was verified that the frame rate was unaffected even in the situation that the number of detected feature points continuously increased.