• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.9
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• pp.45-53
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• 2006

This paper proposes a method for an effective intelligent route decision for automatic moving robots(AMR) using a 2D spatial map of a stereo camera system. In this method, information about depth and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle is detected, and a 2D spatial map is obtained from the location coordinates. Then the relative distances between the obstacle and other objects are deduced. The robot move automatically by effective and intelligent route decision using the obtained 2D spatial map. From experiments on robot driving with 240 frames of stereo images, it was found that the error ratio of the calculated distance to the measured distance between objects was very low, 1.52[%] on average.

• International Journal of Internet, Broadcasting and Communication
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• v.8 no.4
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• pp.54-57
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• 2016

In this paper, the method for an effective and intelligent route decision of the automatic ground vehicle (AGV) using a 2D spatial map of the stereo camera system is proposed. The depth information and disparity map are detected in the inputting images of a parallel stereo camera. The distance between the automatic moving robot and the obstacle detected and the 2D spatial map obtained from the location coordinates, and then the relative distance between the obstacle and the other objects obtained from them. The AGV moves automatically by effective and intelligent route decision using the obtained 2D spatial map. From some experiments on robot driving with 480 frames of the stereo images, it is analyzed that error ratio between the calculated and measured values of the distance between the objects is found to be very low value of 1.57% on average, respectably.

• The Journal of Korea Robotics Society
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• v.1 no.2
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• pp.180-187
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• 2006

This paper presents a new sensor system, CALOS, for motion estimation and 3D reconstruction. The 2D laser sensor provides accurate depth information of a plane, not the whole 3D structure. On the contrary, the CCD cameras provide the projected image of whole 3D scene, not the depth of the scene. To overcome the limitations, we combine these two types of sensors, the laser sensor and the CCD cameras. We develop a motion estimation scheme appropriate for this sensor system. In the proposed scheme, the motion between two frames is estimated by using three points among the scan data and their corresponding image points, and refined by non-linear optimization. We validate the accuracy of the proposed method by 3D reconstruction using real images. The results show that the proposed system can be a practical solution for motion estimation as well as for 3D reconstruction.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.6
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• pp.25-32
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• 1994

A new projection-based approach derived from the Radon transform for detecting and estimating 3-D locations of unresolved targets in a time-sequential set of infrared imageries is presented. Since the signal-to-noise ration per pixel is very low (a dim target) and target tracks which span over many image frames. Since the 2-D multiple representations along arbitary orientations utilizing the 3-D Radon transform, our projection-based transform method enables us to analyze the 3-D problem in terms of its 2-D projections. Our method not only alleviates the great computatioonal expense of processing entire set of images as a whole, but the results reveal that the proposed strategy produces a robust detection and estimation of 3-D target trajectories event at low SNRs.

• Earthquakes and Structures
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• v.6 no.4
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• pp.409-436
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• 2014

Although it is widely accepted that the interaction -between masonry infill and structural members significantly affects the seismic response of reinforced concrete (RC) frames, this interaction is generally neglected in current design-oriented seismic analyses of structures. Moreover, the role of masonry infill is expected to be even more relevant in the case of existing frames designed only for gravitational loads, as infill walls can significantly modify both lateral strength and stiffness. However, the additional contribution to both strength and stiffness is often coupled to a modification of the global collapse mechanisms possibly resulting in brittle failure modes, generally related to irregular distributions of masonry walls throughout the frame. As a matter of principle, accurate modelling of masonry infill should be at least carried out by adopting nonlinear 2D elements. However, several practice-oriented proposals are currently available for modelling masonry infill through equivalent (nonlinear) strut elements. The present paper firstly outlines some of the well-established models currently available in the scientific literature for modelling infill panels in seismic analyses of RC frames. Then, a parametric analysis is carried out in order to demonstrate the consequences of considering such models in nonlinear static and dynamic analyses of existing RC structures. Two bay-frames with two-, three- and four-storeys are considered for performing nonlinear analyses aimed at investigating some critical aspects of modelling masonry infill and their effects on the structural response. Particularly, sensitivity analyses about specific parameters involved in the definition of the equivalent strut models, such as the constitutive force-displacement law of the panel, are proposed.

• The Journal of the Korea Contents Association
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• v.8 no.2
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• pp.18-26
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• 2008

This paper presents a phased visualization method of facial expression space that enables the user to control facial expression of 3D avatars by select a sequence of facial frames from the facial expression space. Our system based on this method creates the 2D facial expression space from approximately 2400 facial expression frames, which is the set of neutral expression and 11 motions. The facial expression control of 3D avatars is carried out in realtime when users navigate through facial expression space. But because facial expression space can phased expression control from radical expressions to detail expressions. So this system need phased visualization method. To phased visualization the facial expression space, this paper use fuzzy clustering. In the beginning, the system creates 11 clusters from the space of 2400 facial expressions. Every time the level of phase increases, the system doubles the number of clusters. At this time, the positions of cluster center and expression of the expression space were not equal. So, we fix the shortest expression from cluster center for cluster center. We let users use the system to control phased facial expression of 3D avatar, and evaluate the system based on the results.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.11
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• pp.789-794
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• 2013

A vehicle tracking system makes it possible to induce the vehicle movement path for avoiding traffic congestion and to prevent traffic accidents in advance by recognizing traffic flow, monitoring vehicles, and detecting road accidents. To track the vehicles effectively, those which appear in a sequence of video frames need to identified by extracting the features of each object in the frames. Next, the identical vehicles over the continuous frames need to be recognized through the matching among the objects' feature values. In this paper, we identify objects by binarizing the difference image between a target and a referential image, and the labelling technique. As feature values, we use the center coordinate of the minimum bounding rectangle(MBR) of the identified object and the averages of 1D FFT(fast Fourier transform) coefficients with respect to the horizontal and vertical direction of the MBR. A vehicle is tracked in such a way that the pair of objects that have the highest similarity among objects in two continuous images are regarded as an identical object. The experimental result shows that the proposed method outperforms the existing methods that use geometrical features in tracking accuracy.

• Journal of Digital Convergence
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• v.14 no.12
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• pp.209-215
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• 2016

The quantity of image frames, the widths of transparent slits, and the black bars on the scanline are the three basic elements of scanimation. Besides, the size of scanimation, the color and contrast of scanimation, and the brightness of scanline, etc, can also influence the optical illusion of scanimation. Based on the recent principle of production of 2D scanimation, and through asking questions, and making corresponding experiment, this research finally gets to the conclusion. Based on the principle of production of 3D scanimation, and through various basic testing, this paper aims to verify how to bring out the best visual effects (optical illusion) of animated illusion scanimation in publications by using the 3D animation in the publications. And the future goal is to study and flexibly use Z-axis space in the scanimation.

• International Journal of Contents
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• v.10 no.3
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• pp.9-16
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• 2014

Depth-image-based rendering is generally used in real-time 2D-to-3D conversion for 3DTV. However, inaccurate depth maps cause flickering issues between image frames in a video sequence, resulting in eye fatigue while viewing 3DTV. To resolve this flickering issue, we propose a new 2D-to-3D conversion scheme based on fast and robust depth-map generation from a 2D video sequence. The proposed depth-map generation algorithm divides an input video sequence into several cuts using a color histogram. The initial depth of each cut is assigned based on a hypothesized depth-gradient model. The initial depth map of the current frame is refined using color and motion information. Thereafter, the depth map of the next frame is updated using the difference image to reduce depth flickering. The experimental results confirm that the proposed scheme performs real-time 2D-to-3D conversions effectively and reduces human eye fatigue.

• Journal of Information Processing Systems
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• v.15 no.2
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• pp.399-409
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• 2019

Three-dimensional (3D) human pose reconstruction from single-view image is a difficult and challenging topic. Existing approaches mostly process frame-by-frame independently while inter-frames are highly correlated in a sequence. In contrast, we introduce a novel spatial-temporal 3D human pose reconstruction framework that leverages both intra and inter-frame relationships in consecutive 2D pose sequences. Orthogonal matching pursuit (OMP) algorithm, pre-trained pose-angle limits and temporal models have been implemented. Several quantitative comparisons between our proposed framework and recent works have been studied on CMU motion capture dataset and Vietnamese traditional dance sequences. Our framework outperforms others by 10% lower of Euclidean reconstruction error and more robust against Gaussian noise. Additionally, it is also important to mention that our reconstructed 3D pose sequences are more natural and smoother than others.