• Title/Summary/Keyword: image correspondence

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Stereo Correspondence Algorithm Using Dynamic programming (동적 계획법을 이용한 스테레오 대응 알고리즘)

  • 이충환;홍석교
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.310-310
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    • 2000
  • The main problem in stereo vision is to find corresponding points in left and right image known as correspondence problem. Once correspondences determined, the depth information of those points are easily computed form the pairs of points in both image. In this paper, dynamic programming considering half-occluded region is used fer solving correspondence problem.

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Camera Focal Length Measuring Method and 3-Dimension Image Correspondence of the Axial Motion Model on Stereo Computer Vision (3-Dimension 영상을 이용한 카메라 초점측정 및 동일축 이동 모델의 영상 정합)

  • 정기룡
    • Journal of the Korean Institute of Navigation
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    • v.16 no.3
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    • pp.77-85
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    • 1992
  • Camera arrangement for depth and image correspondence is very important to the computer vision. Two conventional comera arrangements for stereo computer vision are lateral model and axial motion model. In this paper, using the axial motion stereo camera model, the algorithm for camera focal length measurement and the surface smoothness with the radiance-irradiance is proposed fro 3-dimensional image correspondence on stereo computer vision. By adapting the above algorithm, camera focal length can be measured precisely and the resolution of 3-dimensional image correspondence has been improved comparing to that of the axial motion model without the radiance-irradiance relation.

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A study on correspondence problem of stereo vision system using self-organized neural network

  • Cho, Y.B.;Gweon, D.G.
    • Journal of the Korean Society for Precision Engineering
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    • v.10 no.4
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    • pp.170-179
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    • 1993
  • In this study, self-organized neural network is used to solve the vorrespondence problem of the axial stereo image. Edge points are extracted from a pair of stereo images and then the edge points of rear image are assined to the output nodes of neural network. In the matching process, the two input nodes of neural networks are supplied with the coordi- nates of the edge point selected randomly from the front image. This input data activate optimal output node and its neighbor nodes whose coordinates are thought to be correspondence point for the present input data, and then their weights are allowed to updated. After several iterations of updating, the weights whose coordinates represent rear edge point are converged to the coordinates of the correspondence points in the front image. Because of the feature map properties of self-organized neural network, noise-free and smoothed depth data can be achieved.

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Examining Kansei design keywords in Human Design technology (1)

  • Matsunobe, Takuo;Doi, Atsushi;Yamaoka, Toshiki
    • Proceedings of the Korean Society for Emotion and Sensibility Conference
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    • 2000.04a
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    • pp.189-190
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    • 2000
  • The purpose of this study is to estimate of design and ambience of goods by using 5 Kansei design items (shape, color, sense of material, fit, functionality/convenience). This paper describe that effectiveness of 5 Kansei design items. selecting image words and correspondence of 5 Kansei design items with image words. Kansei design items, selecting image words and correspondence of 5 Kansei design items with image words. (image words: the word describing about item image)

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Multiple Camera-Based Correspondence of Ground Foot for Human Motion Tracking (사람의 움직임 추적을 위한 다중 카메라 기반의 지면 위 발의 대응)

  • Seo, Dong-Wook;Chae, Hyun-Uk;Jo, Kang-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.8
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    • pp.848-855
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    • 2008
  • In this paper, we describe correspondence among multiple images taken by multiple cameras. The correspondence among multiple views is an interesting problem which often appears in the application like visual surveillance or gesture recognition system. We use the principal axis and the ground plane homography to estimate foot of human. The principal axis belongs to the subtracted silhouette-based region of human using subtraction of the predetermined multiple background models with current image which includes moving person. For the calculation of the ground plane homography, we use landmarks on the ground plane in 3D space. Thus the ground plane homography means the relation of two common points in different views. In the normal human being, the foot of human has an exactly same position in the 3D space and we represent it to the intersection in this paper. The intersection occurs when the principal axis in an image crosses to the transformed ground plane from other image. However the positions of the intersection are different depend on camera views. Therefore we construct the correspondence that means the relationship between the intersection in current image and the transformed intersection from other image by homography. Those correspondences should confirm within a short distance measuring in the top viewed plane. Thus, we track a person by these corresponding points on the ground plane. Experimental result shows the accuracy of the proposed algorithm has almost 90% of detecting person for tracking based on correspondence of intersections.

Hierarchical 3D Sgmentation of Image Sequence Using Motion Information Based on Mathematical Morphology (수리 형태학 기반의 움직임 정보를 이용한 연속영상의 계층적 3차원 분할)

  • 여영준;송근원;박영식;김기석;하영호
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.7
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    • pp.78-88
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    • 1997
  • A three dimensional-two spatical dimensions plus time-image segmentation is widely used in a very low bit rate image sequence coding because it can solve the region correspondence problem. Mathematical morphology is a very efficient tool for the segmentation because it deals well with geometric features such as size, shape, contrast and connectivity. But if the motion in the image sequence is large in time axis, the conventional 3D morphological segmentation algorithm have difficulty in solving region correspondence problem. To alleviate this problem, we propose the hierarchical image sequence segmentation algorithm that uses the region motion information. Since the motion of a region in previous level affects that in current level uses the previous motion information to increase region correspondence. Simulation result shows improved performance for sequence frames with large motion.

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A feature-based motion parameter estimation using bi-directional correspondence scheme (쌍방향 대응기법을 이용한 특징점 기반 움직임 계수 추정)

  • 서종열;김경중;임채욱;박규태
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.11
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    • pp.2776-2788
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    • 1996
  • A new feature-based motion parameter estimation for arbitrary-shaped regions is proposed. Existing motion parameter estimation algorithms such as gradient-based algorithm require iterations that are very sensitive to initial values and which often converge to a local minimum. In this paper, the motion parameters of an object are obtained by solving a set of linear equations derived by the motion of salient feature points of the object. In order to estimate the displacement of the feature points, a new process called the "bi-directional correspondence scheme" is proposed to ensure the robjstness of correspondence. The proposed correspondence scheme iteratively selects the feature points and their corresponding points until unique one-to-one correspondence is established. Furthermore, initially obtained motion paramerters are refined using an iterative method to give a better performance. The proposed algorithm can be used for motion estimationin object-based image coder, and the experimental resuls show that the proposed method outperforms existing schemes schemes in estimating motion parameters of objects in image sequences.sequences.

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Correspondence Matching of Stereo Images by Sampling of Planar Region in the Scene Based on RANSAC (RANSAC에 기초한 화면내 평면 영역 샘플링에 의한 스테레오 화상의 대응 매칭)

  • Jung, Nam-Chae
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.4
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    • pp.242-249
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    • 2011
  • In this paper, the correspondence matching method of stereo images was proposed by means of sampling projective transformation matrix in planar region of scene. Though this study is based on RANSAC, it does not use uniform distribution by random sampling in RANSAC, but use multi non-uniform computed from difference in positions of feature point of image or templates matching. The existing matching method sampled that the correspondence is presumed to correct by use of the condition which the correct correspondence is almost satisfying, and applied RANSAC by matching the correspondence into one to one, but by sampling in stages in multi probability distribution computed for image in the proposed method, the correct correspondence of high probability can be sampled among multi correspondence candidates effectively. In the result, we could obtain many correct correspondence and verify effectiveness of the proposed method in the simulation and experiment of real images.

Panoramic Image Stitching using SURF

  • You, Meng;Lim, Jong-Seok;Kim, Wook-Hyun
    • Journal of the Institute of Convergence Signal Processing
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    • v.12 no.1
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    • pp.26-32
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    • 2011
  • This paper proposes a new method to process panoramic image stitching using SURF(Speeded Up Robust Features). Panoramic image stitching is considered a problem of the correspondence matching. In computer vision, it is difficult to find corresponding points in variable environment where a scale, rotation, view point and illumination are changed. However, SURF algorithm have been widely used to solve the problem of the correspondence matching because it is faster than SIFT(Scale Invariant Feature Transform). In this work, we also describe an efficient approach to decreasing computation time through the homography estimation using RANSAC(random sample consensus). RANSAC is a robust estimation procedure that uses a minimal set of randomly sampled correspondences to estimate image transformation parameters. Experimental results show that our method is robust to rotation, zoom, Gaussian noise and illumination change of the input images and computation time is greatly reduced.

Registration of Aerial Image with Lines using RANSAC Algorithm

  • Ahn, Y.;Shin, S.;Schenk, T.;Cho, W.
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.25 no.6_1
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    • pp.529-536
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    • 2007
  • Registration between image and object space is a fundamental step in photogrammetry and computer vision. Along with rapid development of sensors - multi/hyper spectral sensor, laser scanning sensor, radar sensor etc., the needs for registration between different sensors are ever increasing. There are two important considerations on different sensor registration. They are sensor invariant feature extraction and correspondence between them. Since point to point correspondence does not exist in image and laser scanning data, it is necessary to have higher entities for extraction and correspondence. This leads to modify first, existing mathematical and geometrical model which was suitable for point measurement to line measurements, second, matching scheme. In this research, linear feature is selected for sensor invariant features and matching entity. Linear features are incorporated into mathematical equation in the form of extended collinearity equation for registration problem known as photo resection which calculates exterior orientation parameters. The other emphasis is on the scheme of finding matched entities in the aide of RANSAC (RANdom SAmple Consensus) in the absence of correspondences. To relieve computational load which is a common problem in sampling theorem, deterministic sampling technique and selecting 4 line features from 4 sectors are applied.