• Title/Summary/Keyword: 3D Model Registration

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Automatic Registration of Point Cloud Data between MMS and UAV using ICP Method (ICP 기법을 이용한 MSS 및 UAV 간 점군 데이터 자동정합)

  • KIM, Jae-Hak;LEE, Chang-Min;KIM, Hyeong-Joon;LEE, Dong-Ha
    • Journal of the Korean Association of Geographic Information Studies
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    • v.22 no.4
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    • pp.229-240
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    • 2019
  • 3D geo-spatial model have been widely used in the field of Civil Engineering, Medical, Computer Graphics, Urban Management and many other. Especially, the demand for high quality 3D spatial information such as precise road map construction has explosively increased, MMS and UAV techniques have been actively used to acquire them more easily and conveniently in surveying and geo-spatial field. However, in order to perform 3D modeling by integrating the two data set from MMS and UAV, its so needed an proper registration method is required to efficiently correct the difference between the raw data acquisition sensor, the point cloud data generation method, and the observation accuracy occurred when the two techniques are applied. In this study, we obtained UAV point colud data in Yeouido area as the study area in order to determine the automatic registration performance between MMS and UAV point cloud data using ICP(Iterative Closet Point) method. MMS observations was then performed in the study area by dividing 4 zones according to the level of overlap ratio and observation noise with based on UAV data. After we manually registered the MMS data to the UAV data, then compared the results which automatic registered using ICP method. In conclusion, the higher the overlap ratio and the lower the noise level, can bring the more accurate results in the automatic registration using ICP method.

Fast Structure Recovery and Integration using Improved Scaled Orthographic Factorization (개선된 직교분해기법을 사용한 빠른 구조 복원 및 융합)

  • Park, Jong-Seung;Yoon, Jong-Hyun
    • Journal of Korea Multimedia Society
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    • v.10 no.3
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    • pp.303-315
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    • 2007
  • This paper proposes a 3D structure recovery and registration method that uses four or more common points. For each frame of a given video, a partial structure is recovered using tracked points. The 3D coordinates, camera positions and camera directions are computed at once by our improved scaled orthographic factorization method. The partially recovered point sets are parts of a whole model. A registration of point sets makes the complete shape. The recovered subsets are integrated by transforming each coordinate system of the local point subset into a common basis coordinate system. The process of shape recovery and integration is performed uniformly and linearly without any nonlinear iterative process and without loss of accuracy. The execution time for the integration is significantly reduced relative to the conventional ICP method. Due to the fast recovery and registration framework, our shape recovery scheme is applicable to various interactive video applications. The processing time per frame is under 0.01 seconds in most cases and the integration error is under 0.1mm on average.

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Development of a 3D Whole Body Scanner for Reconstructing Human Body based on Contour Triangulation Technique (인체 모델 생성을 위한 등고선 삼각분할 기반의 3차원 전신 스캐너 개발)

  • 최영규;구본기;최병태
    • Journal of KIISE:Computer Systems and Theory
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    • v.30 no.7_8
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    • pp.397-407
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    • 2003
  • In the past decade, significant effort has been made toward increasing the accuracy and robustness in the three-dimensional scanning methods. In this paper, we introduce a novel laser-stripe, 3D scanning system which was developed to digitize a whole human body. We also suggest a new semi-automatic contour registration method to generate robust contours from the 3D data points acquired by our scanning system. A contour triangulation based surface modoling method was also introduced. Experimental result shows that our system is very robust and efficient for reconstructing overall 3D surface model of a human body.

Implementation of A 3-D Animation System Based on The MPEG-4 SNHC Standard (MPEG-4 SNHC 표준을 따르는 3차원 애니메이션 시스템의 구현)

  • 윤승욱;안정환;전정희;호요성
    • Proceedings of the IEEK Conference
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    • 2002.06d
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    • pp.129-132
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    • 2002
  • In this paper, we propose a 3-D animation system to track and analyze motion of the human object. The proposed system consists of two separate layers: motion analysis layer and 3-D model registration layer. Following the MPEG-4 SNHC standard, we generate object motion using body definition and animation parameters. In the implemented system, we acquire human motion data from a single camera and extract body definition parameters from arbitrary VRML human models.

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Registration System of 3D Footwear data by Foot Movements (발의 움직임 추적에 의한 3차원 신발모델 정합 시스템)

  • Jung, Da-Un;Seo, Yung-Ho;Choi, Jong-Soo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.44 no.6
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    • pp.24-34
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    • 2007
  • Application systems that easy to access a information have been developed by IT growth and a human life variation. In this paper, we propose a application system to register a 3D footwear model using a monocular camera. In General, a human motion analysis research to body movement. However, this system research a new method to use a foot movement. This paper present a system process and show experiment results. For projection to 2D foot plane from 3D shoe model data, we construct processes that a foot tracking, a projection expression and pose estimation process. This system divide from a 2D image analysis and a 3D pose estimation. First, for a foot tracking, we propose a method that find fixing point by a foot characteristic, and propose a geometric expression to relate 2D coordinate and 3D coordinate to use a monocular camera without a camera calibration. We make a application system, and measure distance error. Then, we confirmed a registration very well.

Robust Watermarking Algorithm for 3D Mesh Models (3차원 메쉬 모델을 위한 강인한 워터마킹 기법)

  • 송한새;조남익;김종원
    • Journal of Broadcast Engineering
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    • v.9 no.1
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    • pp.64-73
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    • 2004
  • A robust watermarking algorithm is proposed for 3D mesh models. Watermark is inserted into the 2D image which is extracted from the target 3D model. Each Pixel value of the extracted 2D image represents a distance from the predefined reference points to the face of the given 3D model. This extracted image is defined as “range image” in this paper. Watermark is embedded into the range image. Then, watermarked 3D mesh is obtained by modifying vertices using the watermarked range Image. In extraction procedure, the original model is needed. After registration between the original and the watermarked models, two range images are extracted from each 3D model. From these images. embedded watermark is extracted. Experimental results show that the proposed algorithm is robust against the attacks such as rotation, translation, uniform scaling, mesh simplification, AWGN and quantization of vertex coordinates.

Development of the 3D Imaging System and Automatic Registration Algorithm for the Intelligent Excavation System (IES) (지능형 굴삭 시스템을 위한 모바일 3D 이미징 시스템 및 자동 정합 알고리즘의 개발)

  • Chae, Myung-Jin;Lee, Gyu-Won;Kim, Jung-Ryul;Park, Jae-Woo;Yoo, Hyun-Seok;Cho, Moon-Young
    • Korean Journal of Construction Engineering and Management
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    • v.10 no.1
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    • pp.136-145
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    • 2009
  • The objective of the Intelligent Excavation System (IES) is to recognize the work environment and produce work plan and automatically control the excavator through integrating sensor and robot technologies. This paper discusses one of the core technologies of IES development project, development of 3D work environment modeling. 3D laser scanner is used for 3-dimensional mathematical model that can be visualized in virtual space in 3D. This paper describes (1) how the most appropriate 3D imaging system has been chosen; (2) the development of user interface and customization of the s/w to control the scanner for IES project; (3) the development of the mobile station for the scanner; (4) and the algorithm for the automatic registration of laser scan segments for IES project. The development system has been tested on the construction field and lessons learned and future development requirements are suggested.

On Shape Recovery of 3D Object from Multiple Range Images (시점이 다른 다수의 거리 영상으로부터 3차원 물체의 형상 복원)

  • Kim, Jun-Young;Yun, Il-Dong;Lee, Sang-Uk
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.37 no.1
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    • pp.1-15
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    • 2000
  • To reconstruct 3- D shape, It is a common strategy to acquire multiple range Images from different viewpoints and integrate them into a common coordinates In this paper, we particularly focus on the registration and integration processes for combining all range Images into one surface model. For the registration, we propose the 2-step registration algorithm, which consists of 2 steps the rough registration step using all data points and the fine registration step using the high-curved data points For the integration, we propose a new algorithm, referred to as ‘multi-registration’ technique, to alleviate the error accumulation problem, which occurs during applying the pair-wise registration to each range image sequentially, in order to transform them into a common reference frame Intensive experiments are performed on the various real range data In experiments, all range images were registered within 1 minutes on Pentium 150MHz PC The results show that the proposed algorithms registrate and integrate multiple range Images within a tolerable error bound in a reasonable computation time, and the total error between all range Images are equalized with our proposed algorithms.

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3D geometric model generation based on a stereo vision system using random pattern projection (랜덤 패턴 투영을 이용한 스테레오 비전 시스템 기반 3차원 기하모델 생성)

  • Na, Sang-Wook;Son, Jeong-Soo;Park, Hyung-Jun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2005.05a
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    • pp.848-853
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    • 2005
  • 3D geometric modeling of an object of interest has been intensively investigated in many fields including CAD/CAM and computer graphics. Traditionally, CAD and geometric modeling tools are widely used to create geometric models that have nearly the same shape of 3D real objects or satisfy designers intent. Recently, with the help of the reverse engineering (RE) technology, we can easily acquire 3D point data from the objects and create 3D geometric models that perfectly fit the scanned data more easily and fast. In this paper, we present 3D geometric model generation based on a stereo vision system (SVS) using random pattern projection. A triangular mesh is considered as the resulting geometric model. In order to obtain reasonable results with the SVS-based geometric model generation, we deal with many steps including camera calibration, stereo matching, scanning from multiple views, noise handling, registration, and triangular mesh generation. To acquire reliable stere matching, we project random patterns onto the object. With experiments using various random patterns, we propose several tips helpful for the quality of the results. Some examples are given to show their usefulness.

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Respiratory Motion Correction on PET Images Based on 3D Convolutional Neural Network

  • Hou, Yibo;He, Jianfeng;She, Bo
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.7
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    • pp.2191-2208
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    • 2022
  • Motion blur in PET (Positron emission tomography) images induced by respiratory motion will reduce the quality of imaging. Although exiting methods have positive performance for respiratory motion correction in medical practice, there are still many aspects that can be improved. In this paper, an improved 3D unsupervised framework, Res-Voxel based on U-Net network was proposed for the motion correction. The Res-Voxel with multiple residual structure may improve the ability of predicting deformation field, and use a smaller convolution kernel to reduce the parameters of the model and decrease the amount of computation required. The proposed is tested on the simulated PET imaging data and the clinical data. Experimental results demonstrate that the proposed achieved Dice indices 93.81%, 81.75% and 75.10% on the simulated geometric phantom data, voxel phantom data and the clinical data respectively. It is demonstrated that the proposed method can improve the registration and correction performance of PET image.