• Proceedings of the Korea Information Processing Society Conference
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• 2014.04a
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• pp.904-907
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• 2014

In this work we present a robust and fast approach to estimate 3D vehicle pose that can provide results under a specific traffic surveillance conditions. Such limitations are expressed by single fixed CCTV camera that is located relatively high above the ground, its pitch axes is parallel to the reference plane and the camera focus assumed to be known. The benefit of our framework that it does not require prior training, camera calibration and does not heavily rely on 3D model shape as most common technics do. Also it deals with a bad shape condition of the objects as we focused on low resolution surveillance scenes. Pose estimation task is presented as PnP problem to solve it we use well known "POSIT" algorithm [1]. In order to use this algorithm at least 4 non coplanar point's correspondence is required. To find such we propose a set of techniques based on model and scene geometry. Our framework can be applied in real time video sequence. Results for estimated vehicle pose are shown in real image scene.

• 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.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.04a
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• pp.109-114
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• 2000

A new method for the determination of camera system rotation and translation from in 3-D space using recursive least square method is presented in this paper. With this method, the calculation of the equation is found by a linear algorithm. Where the equation are either given or be obtained by solving five or more point correspondences. Good results can be obtained in the presence if more than the eight point. A main advantage of this new method is that it decouple rotation and translation, and then reduces computation. With respect to error in the solution point number in the input image data, adding one more feature correspondence to required minimum number improves the solution accuracy drastically. However, further increase in the number of feature correspondence improve the solution accuracy only slowly. The algorithm proposed by this paper is used to make camera system rotation and translation easy to recognize even when camera system attached at end effecter of six degrees of freedom industrial robot manipulator are applied industrial field.

• 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.

• Journal of Korean Elementary Science Education
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• v.35 no.3
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• pp.305-315
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• 2016

The purpose of this paper was to analyze the role of illustrations in elementary textbooks (3~4 grade) of the 2009 revised curriculum of science education in Korea from point of view of aim of science by applying the criteria of 5E inquiry process model for reflecting core aim of the science education. The subjects of the paper was the 105 illustrations in the earth-science domain of elementary science textbooks (3~4 grade) of the 2009 revised curriculum of science education in Korea. The analysis criterion was of two categories, the function of illustration and the role of illustration. the function of illustration was divided into three subcategories such as Exclusiveness type, correspondence type and supplementary type. The role of illustration was divide into five subcategories such as Engagement, Exploration, Explanation, Elaboration and Evaluation. According to results of the illustration analysis are as follows: the result of the function of illustration are exclusiveness type 39, correspondence type 36 and supplementary type 30, the important of point to note is that there are a lot of exclusiveness type considerably. compared with other subjects, this fact indicate character of illustration of the only science textbook. The result of the role of illustration are Engagement 14, exploration 64, explanation 25, elaboration 2 and evaluation 0. This data indicate main role of illustrations in earth-science domain is to help the students to be able to observe and explore. Cross-analysis of the function and role was a significant difference. Role of illustration was evenly distributed within Exclusiveness type on the other hand, the role of illustrations was mainly exploration and explanation in correspondence and supplementary type. Especially, illustration of exploration was mainly correspondence type.

• The Bulletin of The Korean Astronomical Society
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• v.40 no.2
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• pp.29.3-30
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• 2015

We introduce an advanced one-to-one galaxy correspondence method that populates dark matter halos with galaxies by tracing merging histories of most bound member particles (MBPs) identified in simulated virialized halos. To estimate the survival time of a satellite galaxy, we adopt several models of tidal-destruction time derived from an analytic calculation, isolated galaxy simulations, and cosmological simulations. We build mock galaxy samples for each model by using a merging tree information of MBPs from our new Horizon Run 4 N-body simulation from z = 12 to 0. For models of galaxy survival time derived from cosmological and isolated galaxy simulations, about 40% of satellites galaxies merged into a certain halo are survived until z = 0. We compare mock galaxy samples from our MBP-galaxy correspondence scheme and the subhalo-galaxy scheme with SDSS volume-limited galaxy samples around z = 0 with $M_r-5{\log}h$ < -21 and -20. Compared to the subhalo-galaxy correspondence method, our method predicts more satellite galaxies close to their host halo center and larger pairwise peculiar velocity of galaxies. As a result, our method reproduces the observed galaxy group mass function, the number of member galaxies, and the two-point correlation functions while the subhalo-galaxy correspondence method underestimates them.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.485-494
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• 2015

Canonical correspondence analysis is an ordination method used to visualize the relationships among sites, species and environmental variables. However, projection results are fluctuations if the samples slightly change and consistent interpretation on ecological similarity among species tends to be difficult. We use the bootstrap methods for canonical correspondence analysis to solve this problem. The bootstrap method results show that the variations of coordinate points are inversely proportional to the number of observations and coverage rates with bootstrap confidence interval approximates to nominal probabilities.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.6
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• pp.58-67
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• 2009

A correspondence matching is one of the important tasks in computer vision, and it is not easy to find corresponding points in variable environment where a scale, rotation, view point and illumination are changed. A SURF(Speeded Up Robust Features) algorithm have been widely used to solve the problem of the correspondence matching because it is faster than SIFT(Scale Invariant Feature Transform) with closely maintaining the matching performance. However, because SURF considers only gray image and local geometric information, it is difficult to match corresponding points on the image where similar local patterns are scattered. In order to solve this problem, this paper proposes an extended SURF algorithm that uses the invariant color and global geometric information. The proposed algorithm can improves the matching performance since the color information and global geometric information is used to discriminate similar patterns. In this paper, the superiority of the proposed algorithm is proved by experiments that it is compared with conventional methods on the image where an illumination and a view point are changed and similar patterns exist.

• Journal of the Korean Graphic Arts Communication Society
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• v.8 no.1
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• pp.71-87
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• 1990

This paper presents a simple algorithm to obtain three dimensional information of an object. In the preprocessing of the stereo matching,feature point informations of stero image must be less sensitive to noise and well liked the correspondance problem. This paper described a simple technique of struture feature extraction of 3-D object and used edge-end point expanding method for unconnected line instade of Hough transform. The feature such as corner point and their angles are used for matching problem. The experimental results show that the described algorithm is a useful method for stereo correspondence problem.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.1
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• pp.9-18
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• 2018

Recently, the use of image stitching technology has been increasing as the number of contents based on virtual reality increases. Image Stitching is a method for matching multiple images to produce a high resolution image and a wide field of view image. The image stitching is used in various fields beyond the limitation of images generated from one camera. Image Stitching detects feature points and corresponding points to match multiple images, and calculates the homography among images using the RANSAC algorithm. Generally, corresponding points are needed for calculating conversion relation. However, the corresponding points include various types of noise that can be caused by false assumptions or errors about the conversion relationship. This noise is an obstacle to accurately predict the conversion relation. Therefore, RANSAC algorithm is used to construct an accurate conversion relationship from the outliers that interfere with the prediction of the model parameters because matching methods can usually occur incorrect correspondence points. In this paper, we propose an algorithm that extracts more accurate inliers and computes accurate transformation relations by using correspondence point relation information used in RANSAC algorithm. The correspondence point relation information uses distance ratio between corresponding points used in image matching. This paper aims to reduce the processing time while maintaining the same performance as RANSAC.