• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.173-178
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• 2000

Subjective correspondence among visual variables, auditory variables and vibratory feedback to a hand was experimentally examined to improve usability of a remote controller. First, we studied the correspondence among visual variables represented on a screen or auditory variables and the duration of vibratory stimulus to the subjects' hand by subjective evaluation. Subjective rating method was used in ten items; suitability, comprehensibility, ease-to-use, naturalness, variety, activity, usualness, interest, wish-to-use and feeling of pleasure. Second, to show the effects of multi-modal interface using visual sense, the sense of auditory and vibratory sense, we combined positive stereotype of visual variables and auditory variables provided with the first experiment. The results showed some stereotype between visual variables or auditory variables and duration of vibratory stimulus. Some of the variables such as size, direction of motion, hue, brightness of color and volume of sound had high correspondence with the duration of vibration.

• IEIE Transactions on Smart Processing and Computing
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• v.3 no.3
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• pp.118-127
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• 2014

This paper presents an efficient motion and disparity prediction method for multi-view video coding based on the high efficient video coding (HEVC) standard. The proposed method exploits inter-view candidates for effective prediction of the motion or disparity vector to be coded. The inter-view candidates include not only the motion vectors of adjacent views, but also global disparities across views. The motion vectors coded earlier in an adjacent view were found to be helpful in predicting the current motion vector to reduce the number of bits used in the motion vector information. In addition, the proposed disparity prediction using the global disparity method was found to be effective for interview predictions. A multi-view version based on HEVC was used to evaluate the proposed algorithm, and the proposed correspondence prediction method was implemented on a multi-view platform based on HEVC. The proposed algorithm yielded a coding gain of approximately 2.9% in a high efficiency configuration random access mode.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.8
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• pp.848-855
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• 2008

In this paper, we describe correspondence among multiple images taken by multiple cameras. The correspondence among multiple views is an interesting problem which often appears in the application like visual surveillance or gesture recognition system. We use the principal axis and the ground plane homography to estimate foot of human. The principal axis belongs to the subtracted silhouette-based region of human using subtraction of the predetermined multiple background models with current image which includes moving person. For the calculation of the ground plane homography, we use landmarks on the ground plane in 3D space. Thus the ground plane homography means the relation of two common points in different views. In the normal human being, the foot of human has an exactly same position in the 3D space and we represent it to the intersection in this paper. The intersection occurs when the principal axis in an image crosses to the transformed ground plane from other image. However the positions of the intersection are different depend on camera views. Therefore we construct the correspondence that means the relationship between the intersection in current image and the transformed intersection from other image by homography. Those correspondences should confirm within a short distance measuring in the top viewed plane. Thus, we track a person by these corresponding points on the ground plane. Experimental result shows the accuracy of the proposed algorithm has almost 90% of detecting person for tracking based on correspondence of intersections.

• Korean Journal of Computational Design and Engineering
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• v.16 no.4
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• pp.249-259
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• 2011

In this paper we present our work on the parameterized construction of virtual drivers' reach motion to seat belt, by using motion capture data. A user can generate a new reach motion by controlling a number of parameters. We approach the problem by using multiple sets of example reach motions and learning the relation between the labeling parameters and the motion data. The work is composed of three tasks. First, we construct a motion database using multiple sets of labeled motion clips obtained by using a motion capture device. This involves removing the redundancy of each motion clip by using PCA (Principal Component Analysis), and establishing temporal correspondence among different motion clips by automatic segmentation and piecewise time warping of each clip. Next, we compute motion blending functions by learning the relation between labeling parameters (age, hip base point (HBP), and height) and the motion parameters as represented by a set of PC coefficients. During runtime, on-line motion synthesis is accomplished by evaluating the motion blending function from the user-supplied control parameters.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.1
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• pp.9-16
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• 2002

This paper proposes a new 3D modeling technique using disparity-motion relationship and feature points. To generate the 3D model from real scene, generally, we need to compute depth of model vertices from the dense correspondence map over whole images. It takes much time and is also very difficult to get accurate depth. To improve such problems, in this paper, we only need to find the correspondence of some feature points to generate a 3D model of object without dense correspondence map. The proposed method consists of three parts, which are the extraction of object, the extraction of feature points, and the hierarchical 3D modeling using classified feature points. It has characteristics of low complexity and is effective to synthesize images with virtual view and to express the smoothness of Plain regions and the sharpness of edges.

• ETRI Journal
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• v.36 no.6
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• pp.1008-1015
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• 2014

In this paper, we present a method for reconstructing a surface mesh animation sequence from point cloud animation data. We mainly focus on the articulated body of a subject - the motion of which can be roughly described by its internal skeletal structure. The point cloud data is assumed to be captured independently without any inter-frame correspondence information. Using a template model that resembles the given subject, our basic idea for reconstructing the mesh animation is to deform the template model to fit to the point cloud (on a frame-by-frame basis) while maintaining inter-frame coherence. We first estimate the skeletal motion from the point cloud data. After applying the skeletal motion to the template surface, we refine it to fit to the point cloud data. We demonstrate the viability of the method by applying it to reconstruct a fast dancing motion.

• Journal of the Korea Computer Graphics Society
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• v.20 no.3
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• pp.9-17
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• 2014

This paper presents a method to retarget a source motion to the rig-space parameter for a target character that can be equipped with a complex rig structure as used in traditional animation pipelines. Our solution allows the animators to edit the retargeted motion easily and intuitively as they can work with the same rig parameters that have been used for keyframe animation. To acheive this, we analyze the correspondence between the source motion space and the target rig-space, followed by performing non-linear optimization for the motion retargeting to target rig-space. We observed the general workflow practiced by animators and apply this process to the optimization step.

• 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.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1251-1253
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• 1996

The vision processing system for mobile robots requires real time processing and reliability for the purpose of safe navigation. But, general types of vision systems are not appropriate owing to the correspondence problem which correlates the points out of two images. To determine the obstacle area, we use correspondences of line segments between two perspective images sequentially acquired by camera. To simplify the correspondence, the matching of line segments are performed in the navigation space, based on the assumption that mobile robot should be navigated in the flat surface and the motion of mobile robot between two frames should be approximately known.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.6
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• pp.25-37
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• 2000

The trajectories of feature points can be defined by the correspondences between points in consecutive frames. 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. The trajectories of feature points are determined by calculating the matching measure, which is defined as the minimum weighted Euclidean distance between two feature points. The weights are automatically updated in order to properly reflect the motion characteristics. We solve the correspondence problem as an optimal graph search problem, considering that the existence of false feature points may have serious effect on the correspondence search. The proposed algorithm finds a local optimal correspondence so that the effect of false feature point 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($m^2n$) in the worst case, where m and n arc the number of feature points in two consecutive frames. By considering false feature points and by properly reflecting motion characteristics, the proposed algorithm can find trajectories correctly and robustly, which has been shown by experimental results.