• Title/Summary/Keyword: 3d depth image

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단일 프레임 영상에서 초점을 이용한 깊이정보 생성에 관한 연구 (A Study on Create Depth Map using Focus/Defocus in single frame)

  • 한현호;이강성;이상훈
    • 디지털융복합연구
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    • 제10권4호
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    • pp.191-197
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    • 2012
  • 본 논문에서는 단일 프레임 영상에서 초점을 이용하여 초기 깊이정보를 추출한 후 입체 영상을 생성하는 방법을 제안하였다. 단일 프레임 영상에서 깊이를 추정하기 위해 원본 영상과 가우시안 필터를 중첩 적용하여 생성된 영상의 비교를 통해 영상의 초점 값을 추출하고 추출된 값을 기반으로 초기 깊이정보를 생성하도록 하였다. 생성된 초기 깊이정보를 Normalized cut을 이용한 객체 분할 결과에 할당하고 각 객체의 깊이를 객체 내 깊이 정보의 평균값으로 보정하여 동일 객체가 같은 깊이 값을 갖도록 하였다. 객체를 제외한 배경 영역은 객체를 제외한 배경 영역의 에지 정보를 이용하여 깊이를 생성하였다. 생성된 깊이를 DIBR(Depth Image Based Rendering)을 이용하여 입체 영상으로 변환하였고 기존 알고리즘을 통해 생성된 영상과 비교 분석하였다.

깊이 영상을 이용한 3D 프린팅 기반 환자 맞춤형 안와 임플란트의 설계 및 제작 (3D Printing Based Patient-specific Orbital Implant Design and Production by Using A Depth Image)

  • 서우덕;김구진
    • 한국멀티미디어학회논문지
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    • 제23권8호
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    • pp.903-914
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    • 2020
  • In this paper, we present a novel algorithm to generate a 3D model of patient-specific orbital implant, which is finally produced by the 3D printer. Given CT (computed tomography) scan data of the defective orbital wall or floor, we compose the depth image of the defect site by using the depth buffering, which is a computer graphics technology. From the depth image, we compute the 3D surface which fills the broken part by interpolating the points around the broken part. By thickening the 3D surface, we get the 3D volume mesh of the orbital implant. Our algorithm generates the patient-specific orbital implant whose shape is accurately coincident to the broken part of the orbit. It provides the significant time efficiency for manufacturing the implant with supporting high user convenience.

Optimized Multiple Description Lattice Vector Quantization Coding for 3D Depth Image

  • Zhang, Huiwen;Bai, Huihui;Liu, Meiqin;Zhao, Yao
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제9권3호
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    • pp.1140-1154
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    • 2015
  • Multiple Description (MD) coding is a promising alternative for the robust transmission of information over error-prone channels. Lattice vector quantization (LVQ) is a significant version of MD techniques to design an MD image coder. However, different from the traditional 2D texture image, the 3D depth image has its own special characteristics, which should be taken into account for efficient compression. In this paper, an optimized MDLVQ scheme is proposed in view of the characteristics of 3D depth image. First, due to the sparsity of depth image, the image blocks can be classified into edge blocks and smooth blocks, which are encoded by different modes. Furthermore, according to the boundary contents in edge blocks, the step size of LVQ can be regulated adaptively for each block. Experimental results validate the effectiveness of the proposed scheme, which show better rate distortion performance compared with the conventional MDLVQ.

HTML5에서 직선의 기울기를 이용한 2D to 3D 입체 이미지 변환 (2D to 3D Anaglyph Image Conversion using Linear Curve in HTML5)

  • 박영수
    • 디지털융복합연구
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    • 제12권12호
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    • pp.521-528
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    • 2014
  • 본 논문에서는 HTML5에서 직선의 기울기를 이용하여 2D 이미지를 3D 입체 이미지로 변환하는 방법을 제안한다. 3D 이미지 변환을 위한 어떠한 정보도 없이 단 하나의 원본 이미지를 좌안과 우안을 위해 RGB 색상을 필터링한다. 사용자는 깊이 값을 설정하기 위해 미리 만들어 놓은 제어 점을 선택한 후 깊이 값을 설정하는 작업을 수행한다. 이렇게 선택된 값들을 반영하여, 이미지 전체와 부분적인 원근감을 갖도록 사용자가 정의한 직선의 기울기를 이용하여 좌안과 우안을 위한 깊이를 부여한 후 Anaglyph 3D 이미지를 자동으로 생성하게 된다. 이 모든 과정이 HTML5를 사용한 웹 환경에서 구현하였기 때문에, 사용자들은 매우 쉽고 편리하게 자신들이 원하는 3D 이미지를 생성할 수 있게 된다.

GPU 가속화를 통한 이미지 특징점 기반 RGB-D 3차원 SLAM (Image Feature-Based Real-Time RGB-D 3D SLAM with GPU Acceleration)

  • 이동화;김형진;명현
    • 제어로봇시스템학회논문지
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    • 제19권5호
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    • pp.457-461
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    • 2013
  • This paper proposes an image feature-based real-time RGB-D (Red-Green-Blue Depth) 3D SLAM (Simultaneous Localization and Mapping) system. RGB-D data from Kinect style sensors contain a 2D image and per-pixel depth information. 6-DOF (Degree-of-Freedom) visual odometry is obtained through the 3D-RANSAC (RANdom SAmple Consensus) algorithm with 2D image features and depth data. For speed up extraction of features, parallel computation is performed with GPU acceleration. After a feature manager detects a loop closure, a graph-based SLAM algorithm optimizes trajectory of the sensor and builds a 3D point cloud based map.

Enhancing Depth Accuracy on the Region of Interest in a Scene for Depth Image Based Rendering

  • Cho, Yongjoo;Seo, Kiyoung;Park, Kyoung Shin
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제8권7호
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    • pp.2434-2448
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    • 2014
  • This research proposed the domain division depth map quantization for multiview intermediate image generation using Depth Image-Based Rendering (DIBR). This technique used per-pixel depth quantization according to the percentage of depth bits assigned in domains of depth range. A comparative experiment was conducted to investigate the potential benefits of the proposed method against the linear depth quantization on DIBR multiview intermediate image generation. The experiment evaluated three quantization methods with computer-generated 3D scenes, which consisted of various scene complexities and backgrounds, under varying the depth resolution. The results showed that the proposed domain division depth quantization method outperformed the linear method on the 7- bit or lower depth map, especially in the scene with the large object.

RAY-SPACE INTERPOLATION BYWARPING DISPARITY MAPS

  • Moriy, Yuji;Yendoy, Tomohiro;Tanimotoy, Masayuki;Fujiiz, Toshiaki
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.583-587
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    • 2009
  • In this paper we propose a new method of Depth-Image-Based Rendering (DIBR) for Free-viewpoint TV (FTV). In the proposed method, virtual viewpoint images are rendered with 3D warping instead of estimating the view-dependent depth since depth estimation is usually costly and it is desirable to eliminate it from the rendering process. However, 3D warping causes some problems that do not occur in the method with view-dependent depth estimation; for example, the appearance of holes on the rendered image, and the occurrence of depth discontinuity on the surface of the object at virtual image plane. Depth discontinuity causes artifacts on the rendered image. In this paper, these problems are solved by reconstructing disparity information at virtual camera position from neighboring two real cameras. In the experiments, high quality arbitrary viewpoint images were obtained.

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Design and Implementation of High-Resolution Integral Imaging Display System using Expanded Depth Image

  • Song, Min-Ho;Lim, Byung-Muk;Ryu, Ga-A;Ha, Jong-Sung;Yoo, Kwan-Hee
    • International Journal of Contents
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    • 제14권3호
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    • pp.1-6
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    • 2018
  • For 3D display applications, auto-stereoscopic display methods that can provide 3D images without glasses have been actively developed. This paper is concerned with developing a display system for elemental images of real space using integral imaging. Unlike the conventional method, which reduces a color image to the level as much as a generated depth image does, we have minimized original color image data loss by generating an enlarged depth image with interpolation methods. Our method was efficiently implemented by applying a GPU parallel processing technique with OpenCL to rapidly generate a large amount of elemental image data. We also obtained experimental results for displaying higher quality integral imaging rather than one generated by previous methods.

2D/3D 동영상 변환을 위한 그룹화된 객체별 깊이 정보의 차등 적용 기법 (Applying differential techniques for 2D/3D video conversion to the objects grouped by depth information)

  • 한성호;홍영표;이상훈
    • 한국산학기술학회논문지
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    • 제13권3호
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    • pp.1302-1309
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    • 2012
  • 본 논문은 2D/3D 동영상 변환을 위한 그룹화된 객체별 깊이 정보의 차등 적용 기법에 관한 연구이다. 기존의 깊이 정보 획득 기법 중 움직임 정보를 깊이 정보로써 사용할 때 움직임이 존재하지 않는 객체의 경우 깊이 정보를 획득할 수 없어 해당 객체의 3D 효과를 얻을 수 없는 문제점이 있다. 본 논문에서는 이러한 문제점을 해결하고자 객체와 배경을 추출하고 객체에 움직임 정보를 이용한 깊이 정보를 할당하는 과정을 거친 후, 배경과 깊이 정보가 할당되지 못한 객체에 깊이 단서 중 하나인 상대적 높이 단서를 이용한 깊이 정보를 할당함으로써 모든 객체에서 3D 효과를 얻을 수 있는 기법을 제안한다. 제안한 기법으로 깊이맵을 생성하여 DIBR(Depth Image Based Rendering)으로 3D 영상을 생성하여 확인한 결과 움직임이 없는 객체에서도 3D 효과를 얻을 수 있음을 확인하였다.

딥러닝기반 입체 영상의 획득 및 처리 기술 동향 (Recent Technologies for the Acquisition and Processing of 3D Images Based on Deep Learning)

  • 윤민성
    • 전자통신동향분석
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    • 제35권5호
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    • pp.112-122
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    • 2020
  • In 3D computer graphics, a depth map is an image that provides information related to the distance from the viewpoint to the subject's surface. Stereo sensors, depth cameras, and imaging systems using an active illumination system and a time-resolved detector can perform accurate depth measurements with their own light sources. The 3D image information obtained through the depth map is useful in 3D modeling, autonomous vehicle navigation, object recognition and remote gesture detection, resolution-enhanced medical images, aviation and defense technology, and robotics. In addition, the depth map information is important data used for extracting and restoring multi-view images, and extracting phase information required for digital hologram synthesis. This study is oriented toward a recent research trend in deep learning-based 3D data analysis methods and depth map information extraction technology using a convolutional neural network. Further, the study focuses on 3D image processing technology related to digital hologram and multi-view image extraction/reconstruction, which are becoming more popular as the computing power of hardware rapidly increases.