• 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.

• 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.

• 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.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.8
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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.

• Journal of the Korean Institute of Intelligent Systems
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• v.2 no.3
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• pp.22-28
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• 1992

One of the challenging problems in dynamic scene analysis is the correspondence problem. Points and lines have been two major entities for establishing the correspondence among suxcessive frmes and gave rise to discrete approach to dynamic scene analysis. SOme researchers take continuous approach to analyse the motion. There it is usually assumed that some sort of region correspondence has already been established. In this paper, we propose a method based on fuzzy membership function for solving region correspondence problem.

• The Journal of the Acoustical Society of Korea
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• v.18 no.2
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• pp.66-76
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• 1999

This paper proposes that can take at high speed the information of binocular disparity with moving translational and forward stereo camera to the extent that does not occur the problem of a correspondence point. It shows that in case of stereo vision with translational motion, can take the information of binocular disparity being devoid of error and putting high confidence in, and that in case of stereo vision with forward motion, can take the horizontal component which can not be detected in common stereo vision. Besides, the stereo vision can be done at high speed due to being bright and small a correspondence point comparing not to do, because a correspondence between right and left images is previously limited. But there are problem that a resonable information of binocular disparity can not be taken, if the vicinity of center of image is in accord with the region of occlusion in stereo vision with forward motion.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.47-51
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• 2005

Using satellite images, an optimal solution to water motion has been presented in this study. Since temperature patterns are suitable tracers in water motion, Sea Surface Temperature (SST) images of Caspian Sea taken by MODIS sensor on board Terra satellite have been used in this study. Two daily SST images with 24 hours time interval are used as input data. Computation of templates correspondence between pairs of images is crucial within motion algorithms using non-rigid body objects. Image matching methods have been applied to estimate water body motion within the two SST images. The least squares matching technique, as a flexible technique for most data matching problems, offers an optimal spatial solution for the motion estimation. The algorithm allows for simultaneous local radiometric correction and local geometrical image orientation estimation. Actually, the correspondence between the two image templates is modeled both geometrically and radiometrically. Geometric component of the model includes six geometric transformation parameters and radiometric component of the model includes two radiometric transformation parameters. Using the algorithm, the parameters are automatically corrected, optimized and assessed iteratively by the least squares algorithm. The method used in this study, has presented more efficient and robust solution compared to the traditional motion estimation schemes.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.803-806
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• 2000

The correspondence problem is known to be difficult to solve because false positives and false negatives almost always exist in real image sequences. In this paper, we propose a robust feature tracking algorithm considering incomplete trajectories such as entering and/or vanishing trajectories. We solve the correspondence problem as the optimal graph search problem, by considering false feature points and by properly reflecting motion characteristics. The proposed algorithm finds a local optimal correspondence so that the effect of false feature points can be minimized in the decision process. The time complexity of the proposed graph search algorithm is given by O(mn) in the best case and O(m$^2$n) in the worst case, where m and n are the number of feature points in two consecutive frames. The proposed algorithm can find trajectories correctly and robustly, which has been shown by experimental results.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.305-310
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• 2010

In this paper, we propose a heuristic algorithm for motion correspondence based on a point series similarity. A point series is a sequence of points which are sorted in the ascending order of their x-coordinate values. The proposed algorithm clusters the points of a previous frame based on their local adjacency. For each group, we construct several potential point series by permuting the points in it, each of which is compared to the point series of the following frame in order to match the set of points through their similarity based on a proximity constraint. The longest common subsequence between two point series is used as global information to resolve the local ambiguity. Experimental results show an accuracy of more than 90% on two image sequences from the PETS 2009 and the CAVIAR data sets.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.673-676
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• 2003

This paper deals with the problem of moving object detection and location in computer vision. We describe a new object-dependent motion analysis method for tracking target in an image sequence taken from a moving platform. We tackle these tasks with three steps. First, we make an active contour model of a target in order to build some of low-energy points, which are called kernels. Then we detect interest points in two windows called tracking windows around a kernel respectively. At the third step, we decide the correspondence of those detected interest points between tracking windows by the probabilistic relaxation method In this algorithm, the detecting process is iterative and begins with the detection of all potential correspondence pair in consecutive image. Each pair of corresponding points is then iteratively recomputed to get a globally optimum set of pairwise correspondences.