• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.3 s.309
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• pp.8-15
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• 2006

Obstacle detection is an important task for many mobile robot applications. The methods using stereo vision and optical flow are computationally expensive. Therefore, this paper presents a vision-based obstacle detection method using only two view images. The method uses a single passive camera and odometry, performs in real-time. The proposed method is an obstacle detection method using 3D reconstruction from taro views. Processing begins with feature extraction for each input image using Dr. Lowe's SIFT(Scale Invariant Feature Transform) and establish the correspondence of features across input images. Using extrinsic camera rotation and translation matrix which is provided by odometry, we could calculate the 3D position of these corresponding points by triangulation. The results of triangulation are partial 3D reconstruction for obstacles. The proposed method has been tested successfully on an indoor mobile robot and is able to detect obstacles at 75msec.

• Journal of Educational Research in Mathematics
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• v.13 no.2
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• pp.123-141
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• 2003

This study investigated the understanding level and the using level of mathematical language for middle school students in terms of Freudenthal' language levels. It was proved that the understanding level task developed by current study for geometric concept had reliability and validity, and that there was the hierarchy of levels on which students understanded mathematical language. The level that students used in explaining mathematical concepts was not interrelated to the understanding level, and was different from answering the right answer according to the sorts of tasks. And, the level of mathematical language that was understood easily as students' thought, was the third level of the understanding levels. Mathematics teachers should consider the students' understanding level and using level, and give students the tasks which students could use their mathematical language confidently.

• Journal of Advanced Research in Ocean Engineering
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• v.1 no.2
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• pp.106-114
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• 2015

In the fabrication of offshore oil and gas facilities, the significance of dimension control is growing continuously. But, it is difficult to determine the deformation of the structure during fabrication by simple lab tests due to the large size and the complicated shape. Strain-boundary method (a kind of shrinkage method) based on the shell element was proposed to predict the welding distortion of a structure effectively. Modeling of weld geometry in shell element is still a difficult task. In this paper, a concept of imaginary temperature pair is introduced to handle the effect of geometric factors such as groove shape, plate thickness and pass number, etc. Single pass imaginary temperature pair formula is derived from the relation between the groove area and the FE mesh size. By considering the contribution of each weld layer to the whole weldment, multi-pass imaginary temperature is also derived. Since the temperature difference represents the distortion increment, cumulative distortion curve can be drawn by integrating the temperature difference. This curve will be a useful solution when engineers meet some problems occurred in the shipyard. A typical example is shown about utilization of this curve. Several verifications are conducted to examine the validity of the proposed methodology. The applicability of the model is also demonstrated by applying it to the fabrication process of the heavy ship block. It is expected that the imaginary temperature model can effectively solve the modeling problem in shell element. It is also expected that the cumulative distortion curve derived from the imaginary temperature can offer useful qualitative information about angular distortion without FE analysis.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.7
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• pp.655-661
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• 2017

It is a very important task to extract character regions contained in various input color images, because characters can provide significant information representing the content of an image. In this paper, we propose a new method for extracting character regions from various input images using MCT features and an AdaBoost algorithm. Using geometric features, the method extracts actual character regions by filtering out non-character regions from among candidate regions. Experimental results show that the suggested algorithm accurately extracts character regions from input images. We expect the suggested algorithm will be useful in multimedia and image processing-related applications, such as store signboard detection and car license plate recognition.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.8
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• pp.455-476
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• 2006

An avatar script language consists of commands set which is used to control avatar behaviors in cyberspace. The script language should be abstract from complex low-level concepts, so that a user can write down a scenario script easily without concerning about physical motion parameters. Also, the script should be defined in a standard format and structure to allow reusing in various implementation tools. In this paper, a layered script language is proposed for avatar behavior representation and control, which consists of task-level behavior, high-level motion and primitive motion script language. The script language of each layer represents behavior elements for a scenario scripting interface, an avatar motion sequence, and geometric information of implementation environment, respectively. Therefore, a user can create a scenario script by abstract behavior interface and a script can be applied to various implementations by the proposed translating process. A presentation domain is chosen for applying the proposed script language and the implementation result shows that the script is flexibly applied in several applications.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.515-520
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• 2003

This paper proposes a calibration method from two images. Camera calibration is necessarily required to obtain 3D Information from 2D images. Previous works to accomplish the camera calibration needed the calibration object or required more than three images to calculate the Kruppa equation, however, we use the geometric constraints of parallelism and orthogonality can be easily presented in man-made scenes. The task of it is to obtain intrinsic and extrinsic camera parameters. The intrinsic parameters are evaluated from vanishing points and then the extrinsic parameters which are consisted of rotation matrix and translation vector of the camera are estimated from corresponding points of two views. From the calibrated parameters, we can recover the projection matrices for each view point. These projection matrices are used to recover 3D information of the scene and can be used to visualize new viewpoints.

• Journal of the Korea Society of Computer and Information
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• v.10 no.3 s.35
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• pp.173-182
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• 2005

In this paper, we propose a landmark recognition method which is irrelevant to the camera viewpoint on the navigation for localization. Features in previous research is variable to camera viewpoint, therefore due to the wealth of information, extraction of visual landmarks for positioning is not an easy task. The proposed method in this paper, has the three following stages; first, extraction of features, second, learning and recognition, third, matching. In the feature extraction stage, we set the interest areas of the image. where we extract the corner points. And then, we extract features more accurate and resistant to noise through statistical analysis of a small eigenvalue. In learning and recognition stage, we form robust feature models by testing whether the feature model consisted of five corner points is an invariant feature irrelevant to viewpoint. In the matching stage, we reduce time complexity and find correspondence accurately by matching method using similarity evaluation function and Graham search method. In the experiments, we compare and analyse the proposed method with existing methods by using various indoor images to demonstrate the superiority of the proposed methods.

• Journal of the Korea Computer Graphics Society
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• v.17 no.3
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• pp.9-19
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• 2011

Computing triangle-triangle intersections has been a fundamental task required for many 3D geometric problems. We propose a novel robust GPU algorithm to efficiently compute intersections in a large triangle set. The algorithm has three stages:k-d tree construction, triangle pair generation, and exact intersection computation. All three stages are executed on GPU except, for unsafe triangle pairs. Unsafe triangle pairs are robustly handled by CLP(controlled linear perturbation) on a CPU thread. They are identified by floating-point filtering while exact intersection is computed on GPU. Many triangles crossing a split plane are duplicated in k-d tree construction, which form a lot of redundant triangle pairs later. To eliminate them efficiently, we use a split index which can determine redundancy of a pair by a simple bitwise operation. We applied the proposed algorithm to computing 3D Minkowski sum boundaries to verify its efficiency and robustness.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.6
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• pp.785-791
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• 2021

In this paper, we propose a methodology for estimating the optimal traversable destination from the location-based information of the object recognized by the mobile robot to perform the object delivery service. The location estimation process is to apply the generalized Voronoi graph to the grid map to create an initial topology map composed of nodes and links, recognize objects and extract location data using RGB-D sensors, and collect the shape and distance information of obstacles. Then, by applying the hybrid approach that combines the center of gravity and thinning method, the optimal moving position for the service robot to perform the task of grabbing is estimated. And then, the optimal node information for the robot's work destination is updated by comparing the geometric distance between the estimated position and the existing node according to the node update rule.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.704-713
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• 2021

This paper proposes a method to prioritize the virtual objects to be selected, considering both the user's hand and the geometric relationship with the virtual objects and the user's intention which is recognized in advance. Picking up virtual objects in VR content is an essential and most commonly used interaction. When virtual objects are located close to each other in VR, a situation occurs in which virtual objects that are different from the user's intention are selected. To address this issue, this paper provides different weights for user intentions and distance between user's hand and virtual objects to derive priorities in order to generate interactions appropriately according to the situation. We conducted the experiment in the situation where the number of virtual objects and the distance between virtual objects are diversified. Experiments demonstrate the effectiveness of the proposed method when the density between virtual objects is high and the distance between each other is close, user satisfaction increases to 20.34% by increasing the weight ratio of the situation awareness. We expect the proposed method to contribute to improving interaction skills that can reflect users' intentions.