• The Pure and Applied Mathematics
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• v.6 no.1
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• pp.1-8
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• 1999

Let $K_{\alpha}(G)$ (resp. $K_s(G)$) be the abelian (resp. symmetric) Kac algebra for a locally compact group G. We show that there exists a one-to-one correspondence between the subgroups of G and the sub-Kac algebras of $K_{\alpha}(G)$ (resp. $K_s(G)$). Moreover we obtain similar correspondences between the subgroups of G and the reduced Kac algebras of $K_{\alpha}(G)$ (resp. $K_s(G)$).

• The KIPS Transactions:PartB
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• v.17B no.3
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• pp.215-226
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• 2010

The structured-light 3D reconstruction technique uses a coded-pattern to find correspondences between the camera image and the projector image. To calculate the 3D coordinates of the correspondences, it is necessary to calibrate the camera and the projector. In addition, the calibration results affect the accuracy of the 3D reconstruction. Conventional camera-projector calibration techniques commonly require either expensive hardware rigs or complex algorithm. In this paper, we propose an easy camera-projector calibration technique. The proposed technique does not need any hardware rig or complex algorithm. Thus it will enhance the efficiency of structured-light 3D reconstruction. We present two camera-projector systems to show the calibration results. Error analysis on the two systems are done based on the projection error of the camera and the projector, and 3D reconstruction of world reference points.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.762-766
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• 2003

In this paper, we present a new approach to solve the problem of estimating the camera 3-D location and orientation from a matched set of 3-D model and 2-D image features. An iterative least-square method is used to solve both rotation and translation simultaneously. Because conventional methods that solved for rotation first and then translation do not provide good solutions, we derive an error equation using roll-pitch-yaw angle to present the rotation matrix. To minimize the error equation, Levenberg-Marquardt algorithm is introduced with uniform sampling strategy of rotation space to avoid stuck in local minimum. Experimental results using real images are presented.

• 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.

• Proceedings of the IEEK Conference
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• 2000.11d
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• pp.13-16
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• 2000

This paper presents a robust method to combine a collection of images with small fields of view to obtain an image with a large field of view. In the previous works, there are two main areas which one is a cross correlation-based method and the other is a feature-based method. The former is based on motion estimation from video sequences. so there are a problem on rotating a camera about optical axis. In the latter method, it is difficult to match correspondence feature points correctly.'re find correct correspondences, we proposed the geometrical feature model and correspondence filters and the Gaussian distribution weight function to blend the images smoothly. The experiments show that our method is robust and effective.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.6
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• pp.3121-3142
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• 2017

We present a method for 3D shape reconstruction of inextensible deformable surfaces from a single image. The key of our approach is to represent the surface as a 3D triangulated mesh and formulate the reconstruction problem as a sequence of Linear Programming (LP) problems. The LP problem consists of data constraints which are 3D-to-2D keypoint correspondences and shape constraints which are designed to retain original lengths of mesh edges. We use a closed-form method to generate an initial structure, then refine this structure by solving the LP problem iteratively. Compared with previous methods, ours neither involves smoothness constraints nor temporal consistency, which enables us to recover shapes of surfaces with various deformations from a single image. The robustness and accuracy of our approach are evaluated quantitatively on synthetic data and qualitatively on real data.

• Journal of Computing Science and Engineering
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• v.3 no.2
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• pp.109-126
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• 2009

Taxonomies are widely used to classify information, and multiple (possibly competing) taxonomies often exist for the same domain. Given a set of correspondences between two taxonomies, it is often necessary to "merge" the taxonomies, thereby creating a unied taxonomy (e.g., that can then be used by data integration and discovery applications). We present an algorithm for merging taxonomies that have been related using articulations given as RCC-5 constraints. Two taxa Nand M can be related using (disjunctions of) the ve base relations in RCC-5: M; N ${\subseteq}$M; N ${\supseteq}$; N ${\oplus}$M (partial overlap of Nand M); and N ! M (disjointness: N ${\cap}$M = ${\varnothing}$). RCC-5 is increasingly being adopted by scientists to specify mappings between large biological taxonomies. We discuss the properties of the proposed merge algorithm and evaluate our approach using real-world taxonomies.

• The Journal of the Korea Contents Association
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• v.3 no.1
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• pp.58-63
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• 2003

In this paper, an object tracking system in a known environment is proposed. It extracts moving area shaped on objects in video sequences and decides tracks of moving objects. Color invarianoe features are exploited to extract the plausible object blocks and the degree of radial homogeneity, which is utilized as local block feature to find out the block correspondences. The experimental results are given.

• Korean Journal of Mathematics
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• v.9 no.1
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• pp.45-52
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• 2001

Let A denote the set {$a{\in}M_n{\mid}a{\geq}0$, $tr(a)=1$}, $St(M_n)$ the set of all states on $M_n$, and $PS(M_n)$ the set of all pure states on $M_n$. We show that there are one-to-one correspondences between A and $St(M_n)$, and between the set of all extreme points of A and $PS(M_n)$. We find a necessary and sufficient condition for a state on $M_{n1}{\oplus}{\cdots}{\oplus}M_{nk}$ to be extended to a pure state on $M_{n1}+{\cdots}+_{nk}$.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.11b
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• pp.101-109
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• 2002

In this paper, multiple object tracking system in a known environment is proposed. It extracts moving areas shaped on objects in video sequences and detects racks of moving objects. Color invariant co-occurrence matrices are exploited to extract the plausible object blocks and the correspondences between adjacent video frames. The measures of class separability derived from the features of co-occurrence matrices are used to improve the performance of tracking. The experimented results are presented.