• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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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.

• 한국정밀공학회지
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• 제12권8호
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• pp.156-167
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• 1995

In this paper, we propose a 3-D range finding method for situation that stereo camera has small translational motion. Binocular stereo generally tends to produce stereo correspondence errors and needs huge amount of computation. The former drawback is because the additional constraints to regularize the correspondence problem are not always true for every scene. The latter drawback is because they use either correlation or optimization to find correct disparity. We present a method which overcomes these drawbacks by moving the stereo camera actively. The method utilized a motion parallax acquired by monocular motion stereo to restrict the search range of binocular disparity. Using only the uniqueness of disparity makes it possible to find reliable binocular disparity. Experimental results with real scene are presented to demonstrate the effectiveness of this method.

• IEIE Transactions on Smart Processing and Computing
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• 제1권3호
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• pp.161-170
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• 2012

This paper presents an efficient and robust approach for determining the correspondence between unbalanced stereo images. The disparity vectors were used instead of feature points, such as corners, to calculate a correspondence relationship. For a faster and optimal estimation, the vectors were classified into several regions, and the homography of each region was calculated using the RANSAC algorithm. The correspondence image was calculated from the images transformed by each homography. Although it provided good results under normal conditions, it was difficult to obtain reliable results in an unbalanced stereo pair. Therefore, a balancing method is also proposed to minimize the unbalance effects using the histogram specification and structural similarity index. The experimental results showed that the proposed approach outperformed the baseline algorithms with respect to the speed and peak-signal-to-noise ratio. This work can be applied to practical fields including 3D depth map acquisition, fast stereo coding, 2D-to-3D conversion, etc.

• 한국항해학회지
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• 제16권3호
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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.

• 한국정밀공학회지
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• 제10권4호
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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.

• 한국음향학회지
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• 제18권2호
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• pp.66-76
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• 1999

본 논문은 스테레오 카메라를 대응점 문제가 발생하지 않을 만큼 병진 및 전진 이동시켜 고속으로 양안 시차 정보를 획득할 수 있다는 것을 제안한다. 병진 이동하는 스테레오 비전에 있어서 오차가 없고 신뢰성이 높은 시차 정보를 획득할 수 있다는 것과 전진 이동하는 스테레오 비전에 있어서는 통상의 스테레오 비전으로는 검출할 수 없는 수평성분을 획득할 수 있다는 것을 나타낸다. 또한 좌우 화상사이의 대응을 미리 한정하기 때문에 한정하지 않을 때에 비해 대응점이 밝고 작게 되므로 고속으로 스테레오 비전을 행할 수 있다. 그러나 전진 이동하는 스테레오 비전에 있어서 화상중심 부근과 폐색영역이 일치하면 바른 양안 시차 정보를 얻을 수 없는 문제가 있다.

• 대한전자공학회논문지
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• 제27권1호
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• pp.151-163
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• 1990

In this paper, rule-based stereo algorithm is explored to obtain three dimensional information of an object. In the preprocessing of the stereo matching, feature points of stereo images must be less sensitive to noise and well linked. For this purpose, a new feature points detection algorithm is developed. For performing the stereo matching which is most important process of the stereo algorithm, the feature representation of feature points is first described. The feature representation is then used for a rule-based stereo algorithm to determine the correspondence between the input stereo images. Finally, the three dimensional information of the object is determined from the correspondence of the feature points of right and left images.

• 반도체디스플레이기술학회지
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• 제16권2호
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• pp.70-74
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• 2017

Given two stereo images of a scene, it is possible to recover a 3D understanding of the scene. This is the primary way that the human visual system estimates depth. This process is useful in applications like robotics, where depth sensors may be expensive but a pair of cameras is relatively cheap. In this work, we combined our interests to implement a graph cut algorithm for stereo correspondence, and performed evaluation against a baseline algorithm using normalized cross correlation across a variety of metrics. Experimental trials revealed that the proposed descriptor exhibited a significant improvement, compared to the other existing methods.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.41.2-41
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• 2002

The stereo correspondence of two retinal images is one of the most difficult problems in stereo vision because the reconstruction of 3-D scene is a typical visual ill-posed problem. So far there still have been many unsolved problems, one of which is to reconstruct 3-D scene for a monochromatic surface because there is no clue to make a correspondence between two retinal images. We consider this problem with two layered self-organization neural network to simulate the competitive and cooperative interaction of binocular neurons. A...

• 대한기계학회논문집
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• 제19권6호
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• pp.1431-1438
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• 1995

In this paper, we present a multiple-view stereo matching method in case of moving in the direction of optical axis with stereo camera. Also we analyze the obtainable depth precision to show that multiple-view stereo increases the virtual baseline with single-view stereo. This method decides candidate points for correspondence in each image pair and then search for the correct combinations of correspondences among them using the geometrical consistency they must satisfy. Adantages of this method are capability in increasing the accuracy in matching by using the multiple stereo images and less computation due to local processing. This method computes 3-D depth by averaging the depth obtained in each multiple-view stereo. We show that the resulting depth has more precision than depth obtainable by each independent stereo when the position of image feature is uncertain due to image noise. This paper first defines a multipleview stereo agorithm in case of moving in the direction of optical axis with stereo camera and analyze the obtainable precision of computed depth. Then we represent the effect of removing the incorrect matching candidate and precision enhancement with experimental result.