• Title/Summary/Keyword: True 3D Object

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Eye-Catcher : Real-time 2D/3D Mixed Contents Display System

  • Chang, Jin-Wook;Lee, Kyoung-Il;Park, Tae-Soo
    • 한국정보디스플레이학회:학술대회논문집
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    • 2008.10a
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    • pp.51-54
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    • 2008
  • In this paper, we propose a practical method for displaying 2D/True3D mixed contents in real-time. Many companies released their 3D display recently, but the costs of producing True3D contents are still very expensive. Since there are already a lot of 2D contents in the world and it is more effective to mix True3D objects into the 2D contents than making True3D contents directly, people became interested in mixing 2D/True3D contents. Moreover, real-time 2D/True3D mixing is helpful for 3D displays because the scenario of the contents can be easily changed on playback-time by adjusting the 3D effects and the motion of the True3D object interactively. In our system, True3D objects are rendered into multiple view-point images, which are composed with 2D contents by using depth information, and then they are multiplexed with pre-generated view masks. All the processes are performed on a graphics processor. We were still able to play a 2D/True3D mixed contents with Full HD resolution in real-time using a normal graphics processor.

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Fast Digital Hologram Generation Using True 3D Object (실물에 대한 디지털 홀로그램 고속 생성)

  • Kang, Hoon-Jong;Lee, Gang-Sung;Lee, Seung-Hyun
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.34 no.11B
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    • pp.1283-1288
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    • 2009
  • In general, a 3D computer graphic model is being used to generate a digital hologram as theinput information because the 3D information of an object can be extracted from a 3D model, easily. The 3D information of a real scene can be extracted by using a depth camera. The 3D information, point cloud, corresponding to real scene is extracted from a taken image pair, a gray texture and a depth map, by a depth camera. The extracted point cloud is used to generate a digital hologram as input information. The digital hologram is generated by using the coherent holographic stereogram, which is a fast digital hologram generation algorithm based on segmentation. The generated digital hologram using the taken image pair by a depth camera is reconstructed by the Fresnel approximation. By this method, the digital hologram corresponding to a real scene or a real object could be generated by using the fast digital hologram generation algorithm. Furthermore, experimental results are satisfactory.

Synthetic hit-miss transform for optical recognition of a moving target (이동물체의 광학적 인식을 위한 합성 HMT)

  • 김종찬;김정우;이하운;도양회;김수중
    • Journal of the Korean Institute of Telematics and Electronics D
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    • v.35D no.3
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    • pp.82-90
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    • 1998
  • A hit-miss transform(HMT) using synthetic structuring elements(SE's) for optical recognition of a moving target is proposed. A moving target which was obtained from a fixed view point has objects. In proposed HMT, SE's are synthesized by using SDF(synthetic discriminant function) algorithm for efficient recognitionof various shapes of true class objects in noisy and cluttered scene. The synthetic hit SE and the synthetic miss SE are composed of SDF of hit SE's and miss SE's for each true class object. Simulation results show the proposed method can be used for the recognition of various shapes of the true class with one one HMT operation.

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Development of Digital Image Acquisition Technique for Momentary Positioning of Dynamic Object (동체의 순간 위치결정을 위한 수치영상 획득기법 개발)

  • Han, Seung-Hee;Kang, Joon-Mook
    • Journal of Korean Society for Geospatial Information Science
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    • v.4 no.2 s.8
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    • pp.47-54
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    • 1996
  • It needs more than two images which are obtained in real time to decide 3D positioning of dynamic object. Though we use digital camera which is became wide utilization, but it can't obtain sequential image. So, in this study, we constructed momentary image acquisition system using video camera. Also, we took a photograph of LCD timer and dynamic object together for real time stereo image, and we obtained independent digital image from sequential image using video editor. As a result of the study, we could obtain the independent image as true color digital image of $788{\times}550$pixels with 1/100sec accuracy in the same time. And it was good when we tested object target. For comparing 3D positioning accuracy, we could obtained negative with metric camera using B-shutter.

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Key Point Extraction from LiDAR Data for 3D Modeling (3차원 모델링을 위한 라이다 데이터로부터 특징점 추출 방법)

  • Lee, Dae Geon;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.34 no.5
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    • pp.479-493
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    • 2016
  • LiDAR(Light Detection and Ranging) data acquired from ALS(Airborne Laser Scanner) has been intensively utilized to reconstruct object models. Especially, researches for 3D modeling from LiDAR data have been performed to establish high quality spatial information such as precise 3D city models and true orthoimages efficiently. To reconstruct object models from irregularly distributed LiDAR point clouds, sensor calibration, noise removal, filtering to separate objects from ground surfaces are required as pre-processing. Classification and segmentation based on geometric homogeneity of the features, grouping and representation of the segmented surfaces, topological analysis of the surface patches for modeling, and accuracy assessment are accompanied by modeling procedure. While many modeling methods are based on the segmentation process, this paper proposed to extract key points directly for building modeling without segmentation. The method was applied to simulated and real data sets with various roof shapes. The results demonstrate feasibility of the proposed method through the accuracy analysis.

Robust 3-D Motion Estimation Based on Stereo Vision and Kalman Filtering (스테레오 시각과 Kalman 필터링을 이용한 강인한 3차원 운동추정)

  • 계영철
    • Journal of Broadcast Engineering
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    • v.1 no.2
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    • pp.176-187
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    • 1996
  • This paper deals with the accurate estimation of 3- D pose (position and orientation) of a moving object with reference to the world frame (or robot base frame), based on a sequence of stereo images taken by cameras mounted on the end - effector of a robot manipulator. This work is an extension of the previous work[1]. Emphasis is given to the 3-D pose estimation relative to the world (or robot base) frame under the presence of not only the measurement noise in 2 - D images[ 1] but also the camera position errors due to the random noise involved in joint angles of a robot manipulator. To this end, a new set of discrete linear Kalman filter equations is derived, based on the following: 1) the orientation error of the object frame due to measurement noise in 2 - D images is modeled with reference to the camera frame by analyzing the noise propagation through 3- D reconstruction; 2) an extended Jacobian matrix is formulated by combining the result of 1) and the orientation error of the end-effector frame due to joint angle errors through robot differential kinematics; and 3) the rotational motion of an object, which is nonlinear in nature, is linearized based on quaternions. Motion parameters are computed from the estimated quaternions based on the iterated least-squares method. Simulation results show the significant reduction of estimation errors and also demonstrate an accurate convergence of the actual motion parameters to the true values.

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Research of Matching Performance Improvement for DEM generation from Multiple Images (다중 영상으로부터 DEM 생성을 위한 정합기법의 성능향상 연구)

  • Rhee, Soo-Ahm;Kim, Tae-Jung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.1
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    • pp.101-109
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    • 2011
  • This paper describes the attempts to improve the performance of an image matching method for multiple image. Typically, matching between two images is performed by using correlation between a reference and corresponding images. The proposed multiple image matching algorithm performs matching in an object space, chooses the image closest to the true vertical image as a reference image, calculates the correlation based on the chosen reference image. The algorithm also detects occluded regions automatically and keep them from matching. We could find that it is possible to create high quality DEM by this method, regardless of the location of image. From the performance improvement experiments through the occlusion detection, we could confirm the possibility of a more accurate representation of 3D information.

Land cover classification using LiDAR intensity data and neural network

  • Minh, Nguyen Quang;Hien, La Phu
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.29 no.4
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    • pp.429-438
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    • 2011
  • LiDAR technology is a combination of laser ranging, satellite positioning technology and digital image technology for study and determination with high accuracy of the true earth surface features in 3 D. Laser scanning data is typically a points cloud on the ground, including coordinates, altitude and intensity of laser from the object on the ground to the sensor (Wehr & Lohr, 1999). Data from laser scanning can produce products such as digital elevation model (DEM), digital surface model (DSM) and the intensity data. In Vietnam, the LiDAR technology has been applied since 2005. However, the application of LiDAR in Vietnam is mostly for topological mapping and DEM establishment using point cloud 3D coordinate. In this study, another application of LiDAR data are present. The study use the intensity image combine with some other data sets (elevation data, Panchromatic image, RGB image) in Bacgiang City to perform land cover classification using neural network method. The results show that it is possible to obtain land cover classes from LiDAR data. However, the highest accurate classification can be obtained using LiDAR data with other data set and the neural network classification is more appropriate approach to conventional method such as maximum likelyhood classification.

Volumetric accuracy of cone-beam computed tomography

  • Park, Cheol-Woo;Kim, Jin-ho;Seo, Yu-Kyeong;Lee, Sae-Rom;Kang, Ju-Hee;Oh, Song-Hee;Kim, Gyu-Tae;Choi, Yong-Suk;Hwang, Eui-Hwan
    • Imaging Science in Dentistry
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    • v.47 no.3
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    • pp.165-174
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    • 2017
  • Purpose: This study was performed to investigate the influence of object shape and distance from the center of the image on the volumetric accuracy of cone-beam computed tomography (CBCT) scans, according to different parameters of tube voltage and current. Materials and Methods: Four geometric objects(cylinder, cube, pyramid, and hexagon) with predefined dimensions were fabricated. The objects consisted of Teflon-perfluoroalkoxy embedded in a hydrocolloid matrix (Dupli-Coe-Loid TM; GC America Inc., Alsip, IL, USA), encased in an acrylic resin cylinder assembly. An Alphard Vega Dental CT system (Asahi Roentgen Ind. Co., Ltd, Kyoto, Japan) was used to acquire CBCT images. OnDemand 3D (CyberMed Inc., Seoul, Korea) software was used for object segmentation and image analysis. The accuracy was expressed by the volume error (VE). The VE was calculated under 3 different exposure settings. The measured volumes of the objects were compared to the true volumes for statistical analysis. Results: The mean VE ranged from -4.47% to 2.35%. There was no significant relationship between an object's shape and the VE. A significant correlation was found between the distance of the object to the center of the image and the VE. Tube voltage affected the volume measurements and the VE, but tube current did not. Conclusion: The evaluated CBCT device provided satisfactory volume measurements. To assess volume measurements, it might be sufficient to use serial scans with a high resolution, but a low dose. This information may provide useful guidance for assessing volume measurements.

True Orthoimage Generation from LiDAR Intensity Using Deep Learning (딥러닝에 의한 라이다 반사강도로부터 엄밀정사영상 생성)

  • Shin, Young Ha;Hyung, Sung Woong;Lee, Dong-Cheon
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.38 no.4
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    • pp.363-373
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    • 2020
  • During last decades numerous studies generating orthoimage have been carried out. Traditional methods require exterior orientation parameters of aerial images and precise 3D object modeling data and DTM (Digital Terrain Model) to detect and recover occlusion areas. Furthermore, it is challenging task to automate the complicated process. In this paper, we proposed a new concept of true orthoimage generation using DL (Deep Learning). DL is rapidly used in wide range of fields. In particular, GAN (Generative Adversarial Network) is one of the DL models for various tasks in imaging processing and computer vision. The generator tries to produce results similar to the real images, while discriminator judges fake and real images until the results are satisfied. Such mutually adversarial mechanism improves quality of the results. Experiments were performed using GAN-based Pix2Pix model by utilizing IR (Infrared) orthoimages, intensity from LiDAR data provided by the German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) through the ISPRS (International Society for Photogrammetry and Remote Sensing). Two approaches were implemented: (1) One-step training with intensity data and high resolution orthoimages, (2) Recursive training with intensity data and color-coded low resolution intensity images for progressive enhancement of the results. Two methods provided similar quality based on FID (Fréchet Inception Distance) measures. However, if quality of the input data is close to the target image, better results could be obtained by increasing epoch. This paper is an early experimental study for feasibility of DL-based true orthoimage generation and further improvement would be necessary.