• Journal of Korea Multimedia Society
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• v.6 no.5
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• pp.896-908
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• 2003

Interaction technique in .3D virtual environment is a decisive factor that affects the immersion and presence felt by users in virtual space. Especially, in fields that require exquisite manipulation of objects such as electronic manuals in desktop environment, interaction technique that supports effective and natural manipulation of object is in demand. In this paper, 3D scene graph can be internally divided and reconstructed to a list defending on the users selection and through moving focus among the selection candidate objects list, the user can select 3D object more accurately Also, by providing various feedbacks for each manipulation stage, more effective manipulation is possible. The proposed technique can be used as 3D user interface in areas that require exquisite object manipulation.

• Journal of KIISE
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• v.41 no.10
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• pp.838-846
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• 2014

Three-dimensional (3D) object retrieval from user-drawn sketch queries is one of the important research issues in the areas of pattern recognition and computer graphics for simulation, visualization, and Computer Aided Design. The performance of content-based 3D object retrieval system depends on the availability of effective descriptors and similarity measures for this kind of data. In this paper, we present a sketch-based 3D object retrieval system by extracting a hybrid edge descriptor which is robust against rotation and translation. The experimental results which are based on HTML5 and WebGL show that proposed sketch-based 3D object retrieval method is very efficient to search and order the 3D objects according to user's intention.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.878-881
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• 2008

To index the object's trajectory is an important aspect in moving object database management. This paper implements an optimizing index structure named Rend 3D R-tree based on 3D R-Tree. This paper demonstrates the time period update method to reconstruct the MBR for the moving objects in order to decrease the dead space that is produced in the closed time dimension of the 3D R-tree, then a rend method is introduced for indexing both current data and history data. The result of experiments illustrates that given methods outperforms 3D R-Tree and LUR tree in query processes.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.11
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• pp.1482-1484
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• 2019

We present a method for transmitting 3D object information in real time in a telepresence system. Three-dimensional object information consists of a large amount of point cloud data, which requires high performance computing power and ultra-wideband network transmission environment to process and transmit such a large amount of data in real time. In this paper, multiple users can transmit object motion and facial expression information in real time even in small network bands by using GANs (Generative Adversarial Networks), a non-supervised learning machine learning algorithm, for real-time transmission of 3D point cloud data. In particular, we propose the creation of an object similar to the original using only the feature information of 3D objects using conditional GANs.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.5
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• pp.330-337
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• 2022

Research on object detection algorithms using 2D data has already progressed to the level of commercialization and is being applied to various manufacturing industries. Object detection technology using 2D data has an effective advantage, there are technical limitations to accurate data generation and analysis. Since 2D data is two-axis data without a sense of depth, ambiguity arises when approached from a practical point of view. Advanced countries such as the United States are leading 3D data collection and research using 3D laser scanners. Existing processing and detection algorithms such as ICP and RANSAC show high accuracy, but are used as a processing speed problem in the processing of large-scale point cloud data. In this study, PointNet a representative technique for detecting objects using widely used 3D point cloud data is analyzed and described. And RandLA-Net, which overcomes the limitations of PointNet's performance and object prediction accuracy, is described a review of detection technology using point cloud data was conducted.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.8
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• pp.60-70
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• 2000

In this paper a 3D position measuring device that finds the 3D position of an arbitarily placed object using a camersa system is introduced. The camera system consists of three stepping motors and a CCD camera and a laser. The viewing direction of the camera is controlled by two stepping motors (pan and tilt motors) and the direction of a laser is also controlled by a stepping motors(laser motor). If an object in a remote place is selected from a live video image the x,y,z coordinates of the object with respect to the reference coordinate system can be obtained by calculating the distance from the camera to the object using a structured light scheme and by obtaining the orientation of the camera that is controlled by two stepping motors. The angles o f stepping motors are controlled by a SGI O2 workstation through a parallel port. The mathematical model of the camera and the distance measuring system are calibrated to calculate an accurate position of the object. This 3D position measuring device can be used to acquire information that is necessary to monitor a remote place.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.1123-1124
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• 2008

In this paper, we develop a program that recognition of the object 3D pose using stereo camera. In order to detect the object, this paper is applied to canny edge detection algorithm and also used stereo camera to get the 3D point about the object and applied to recognize the pose of the object using iterative closest point(ICP) algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.399-404
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• 1992

Curved 3D objects represented by range data contain large amounts of information compared with planar objects, but do not have distinct features for matching to those of object models. This makes it difficult to represent and identify a general 3D curved object. This paper introduces a new approach to representing and finding a holdsite of general 3D curved objects using range data. We develop a three-dimensional generalized Hough transformation which can be also applied to general 3D curved object recognition and which reduces both the computation time and storage requirements. Our approach makes use of the relative geometric differences between particular points on the object surface and some model points which are prespecified arbitrarily and task dependently.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.173-176
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• 2001

In this study, we designed a virtual gallery using VRML authoring tool. With this system, we expect to provide a realistic and interactive environment where students can appreciate artistic work in their learning processes. Our system is implemented with several methods such as panorama images and 3D object modules with Photo Vista, Object Modeler and Reality Studio. We currently investigate how this virtual gallery can affect students aesthetic aspects with the intended realistic appreciation In their art education processes. In the following section, we describes how we implemented our virtual gallery with vrml authoring tools.

• 한국정보컨버전스학회:학술대회논문집
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• 2008.06a
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• pp.103-110
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• 2008

In this thesis, we describe a statistical method for 3D object detection. In this method, we decompose the 3D geometry of each object into a small number of viewpoints. For each viewpoint, we construct a decision rule that determines if the object is present at that specific orientation. Each decision rule uses the statistics of both object appearance and "non-object" visual appearance. We represent each set of statistics using a product of histograms. Each histogram represents the joint statistics of a subset of wavelet coefficients and their position on the object. Our approach is to use many such histograms representing a wide variety of visual attributes. Using this method, we have developed the first algorithm that can reliably detect faces that vary from frontal view to full profile view and the first algorithm that can reliably detect cars over a wide range of viewpoints.