• The Transactions of the Korea Information Processing Society
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• v.4 no.11
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• pp.2840-2848
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• 1997

Recognition of 3D objects using computer vision is complicated by the fact that geometric features vary with view orientation. An important factor in designing recognition algorithms in such situations is understanding the variation of certain critical features. The features selected in this paper are the angles between landmarks in a scene. In a class of polyhedral objects the angles at certain vertices may form a distinct and characteristic alignment of faces. For many other classes of objects it may be possible to identify distinctive spacial arrangements of some readily identifiable landmarks. In this paper given an isotropic view orientation and an orthographic projection the two dimensional joint density function of two angles in a scene is derived. Also the joint density of all defining angles of a polygon in an image is derived. The analytic expressions for the densities are useful in determining statistical decision rules to recognize surfaces and objects. Experiments to evaluate the usefulness of the proposed methods are reported. Results indicate that the method is useful and powerful.

• 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.

• International conference on construction engineering and project management
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• 2009.05a
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• pp.30-31
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• 2009

Early detection of schedule delay in field construction activities is vital to project management. It provides the opportunity to initiate remedial actions and increases the chance of controlling such overruns or minimizing their impacts. This entails project managers to design, implement, and maintain a systematic approach for progress monitoring to promptly identify, process and communicate discrepancies between actual and as-planned performances as early as possible. Despite importance, systematic implementation of progress monitoring is challenging: (1) Current progress monitoring is time-consuming as it needs extensive as-planned and as-built data collection; (2) The excessive amount of work required to be performed may cause human-errors and reduce the quality of manually collected data and since only an approximate visual inspection is usually performed, makes the collected data subjective; (3) Existing methods of progress monitoring are also non-systematic and may also create a time-lag between the time progress is reported and the time progress is actually accomplished; (4) Progress reports are visually complex, and do not reflect spatial aspects of construction; and (5) Current reporting methods increase the time required to describe and explain progress in coordination meetings and in turn could delay the decision making process. In summary, with current methods, it may be not be easy to understand the progress situation clearly and quickly. To overcome such inefficiencies, this research focuses on exploring application of unsorted daily progress photograph logs - available on any construction site - as well as IFC-based 4D models for progress monitoring. Our approach is based on computing, from the images themselves, the photographer's locations and orientations, along with a sparse 3D geometric representation of the as-built scene using daily progress photographs and superimposition of the reconstructed scene over the as-planned 4D model. Within such an environment, progress photographs are registered in the virtual as-planned environment, allowing a large unstructured collection of daily construction images to be interactively explored. In addition, sparse reconstructed scenes superimposed over 4D models allow site images to be geo-registered with the as-planned components and consequently, a location-based image processing technique to be implemented and progress data to be extracted automatically. The result of progress comparison study between as-planned and as-built performances can subsequently be visualized in the D4AR - 4D Augmented Reality - environment using a traffic light metaphor. In such an environment, project participants would be able to: 1) use the 4D as-planned model as a baseline for progress monitoring, compare it to daily construction photographs and study workspace logistics; 2) interactively and remotely explore registered construction photographs in a 3D environment; 3) analyze registered images and quantify as-built progress; 4) measure discrepancies between as-planned and as-built performances; and 5) visually represent progress discrepancies through superimposition of 4D as-planned models over progress photographs, make control decisions and effectively communicate those with project participants. We present our preliminary results on two ongoing construction projects and discuss implementation, perceived benefits and future potential enhancement of this new technology in construction, in all fronts of automatic data collection, processing and communication.

• IEIE Transactions on Smart Processing and Computing
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• v.4 no.5
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• pp.311-317
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• 2015

The aim of this study is to develop a 3D registration algorithm for positron emission tomography/computed tomography (PET/CT) and magnetic resonance (MR) images acquired from independent PET/CT and MR imaging systems. Combined PET/CT images provide anatomic and functional information, and MR images have high resolution for soft tissue. With the registration technique, the strengths of each modality image can be combined to achieve higher performance in diagnosis and radiotherapy planning. The proposed method consists of two stages: normalized mutual information (NMI)-based global matching and independent component analysis (ICA)-based refinement. In global matching, the field of view of the CT and MR images are adjusted to the same size in the preprocessing step. Then, the target image is geometrically transformed, and the similarities between the two images are measured with NMI. The optimization step updates the transformation parameters to efficiently find the best matched parameter set. In the refinement stage, ICA planes from the windowed image slices are extracted and the similarity between the images is measured to determine the transformation parameters of the control points. B-spline. based freeform deformation is performed for the geometric transformation. The results show good agreement between PET/CT and MR images.

• Proceedings of the CALSEC Conference
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• 2001.08a
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• pp.615-624
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• 2001

Internet technology opens up another domain for building future CAD/CAM environment. The environment will be global, network-centric, and spatially distributed. In this paper, we present a new approach to network-centric virtual prototyping (NetVP) in a distributed design environment. The presented approach combines the current virtual assembly modeling and analysis technique with distributed computing and communication technology fur supporting virtual prototyping activities over the network. This paper focuses on interoperability, shape representation, and geometric processing for distributed virtual prototyping. STEP standard and CORBA-based interfaces allow the bi-directional communication between the CAD model and virtual prototyping model, which makes it possible to solve the problems of interoperability, heterogeneity of platforms, and data sharing. STEP AP203 and AP214 are utilized as a means of transferring and sharing product models. In addition, Attributed Abstracted B-rep (AAB) is introduced as 3D shape abstraction for transparent and efficient transmission of 3D models and for the maintenance of naming consistency between CAD models and virtual prototyping models over the network.

• Korean Journal of Materials Research
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• v.29 no.4
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• pp.264-270
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• 2019

As a case study on aspect ratio behavior, Kaolin, zeolite, $TiO_2$, pozzolan and diatomaceous earth minerals are investigated using wet milling with 0.3 pai media. The grinding process using small media of 0.3 pai is suitable for current work processing applications. Primary particles with average particle size distribution D50, ${\sim}6{\mu}m$ are shifted to submicron size, D50 ${\sim}0.6{\mu}m$, after grinding. Grinding of particles is characterized by various size parameters such as sphericity as geometric shape, equivalent diameter, and average particle size distribution. Herein, we systematically provide an overview of factors affecting the primary particle size reduction. Energy consumption for grinding is determined using classical grinding laws, including Rittinger's and Kick's laws. Submicron size is obtained at maximum frictional shear stress. Alterations in properties of wettability, heat resistance, thermal conductivity, and adhesion increase with increasing particle surface area. In the comparison of the aspect ratio of the submicron powder, the air heat conductivity and the total heat release amount increase 68 % and 2 times, respectively.

• Journal of information and communication convergence engineering
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• v.9 no.2
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• pp.207-211
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• 2011

This paper presents a method for facial feature representation and recognition from the Covariance Matrices of the Gabor-filtered images. Gabor filters are a very powerful tool for processing images that respond to different local orientations and wave numbers around points of interest, especially on the local features on the face. This is a very unique attribute needed to extract special features around the facial components like eyebrows, eyes, mouth and nose. The Covariance matrices computed on Gabor filtered faces are adopted as the feature representation for face recognition. Geodesic distance measure is used as a matching measure and is preferred for its global consistency over other methods. Geodesic measure takes into consideration the position of the data points in addition to the geometric structure of given face images. The proposed method is invariant and robust under rotation, pose, or boundary distortion. Tests run on random images and also on publicly available JAFFE and FRAV3D face recognition databases provide impressively high percentage of recognition.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.1
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• pp.58-63
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• 2006

This paper describes a novel automated analysis system for bellows of piping system. An automatic finite element (FE) mesh generation technique, which is based on the fuzzy theory and computational geometry technique, is incorporated into the system, together with one of commercial FE analysis codes and one of commercial solid modelers. In this system, a geometric model, i.e. an analysis model, is first defined using a commercial solid modelers for 3-D shell structures. Node is generated if its distance from existing node points is similar to the node spacing function at the point. The node spacing function is well controlled by the fuzzy knowledge processing. The Delaunay triangulation technique is introduced as a basic tool for element generation. The triangular elements are converted to quadrilateral elements. Practical performances of the present system are demonstrated through several analysis for bellows of piping system.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.3
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• pp.108-115
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• 2006

In this paper, a recognition algorithm of the straight line components of lane markings and an obstacle in the travelling lane region is proposed. This algorithm also involve the pitching error correction algorithm due to traveling vehicle's fluctuation. In order to reduce their error a practical road image modelling algorithm using V.F. model and camera calibration procedure are suggested to adapt the geometric variations. It is obtained the 3D world coordinate data by the 2D road images. In experimental test, we showed that this algorithm is available to recognize lane markings and an obstacle in the traveling lane.

• The Journal of the Korea Contents Association
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• v.10 no.4
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• pp.106-114
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• 2010

Mesh parameterization is the process of finding one-to-one mapping between an input mesh and a parametric domain. It has been considered as a fundamental tool for digital geometric processing which is required to develop several applications of digital geometries. In this paper, we propose a novel 3D volume parameterization by means that a harmonic mapping is established between a 3D volume mesh and a unit solid cube. To do that, we firstly partition the boundary of the given 3D volume mesh into the six different rectangular patches whose adjacencies are topologically identical to those of a surface cube. Based on the partitioning result, we compute the boundary condition as a precondition for computing a volume mesh parameterization. Finally, the volume mesh parameterization with a low-distortion can be accomplished by performing a harmonic mapping, which minimizes the harmonic energy, with satisfying the boundary condition. Experimental results show that our method is efficient enough to compute 3D volume mesh parameterization for several models, each of whose topology is identical to a solid sphere.