• Title/Summary/Keyword: 구형 파노라마

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Creating Full View Panorama Image from Multiple Images (다중영상으로부터 360도 파노라마 생성)

  • Joe, Jun-Seong;Lee, Bum-Jong;Park, Jong-Seung
    • Proceedings of the Korean Information Science Society Conference
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    • 2007.10b
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    • pp.162-166
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    • 2007
  • 단일 영상의 시야각 한계를 극복하기 위해 다중 영상으로부터 하나의 파노라마 영상으로 만들 수 있다. 파노라마 영상은 좌우 360도까지의 시야각을 확보할 수 있어서 복잡한 실제 환경을 가상 환경에서의 배경으로 사용하고자 할 경우에 유용하다. 본 논문에서는 가상 환경에서의 배경으로 사용할 수 있는 파노라마 영상 생성 기법을 제안한다. 다중 영상들을 촬영하고 이를 사용하여 하나의 구형 파노라마 영상을 생성한다. 상하 시야각을 180도까지 확보하기 위한 제작 기법을 제시한다. 또한 생성된 구형 파노라마 영상으로부터 3차원 렌더링에 적합한 텍스쳐로의 변환과정을 제시한다 실제 환경을 가상화할 시에 파노라마 배경을 사용하면 조밀한 배경을3차원적으로 모델링하지 않고도 배경을 3차원적으로 표현할 수 있으므로 제안된 기법은 가상현실 응용에 유용하게 사용될 수 있다.

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SINGLE PANORAMA DEPTH ESTIMATION USING DOMAIN ADAPTATION (도메인 적응을 이용한 단일 파노라마 깊이 추정)

  • Lee, Jonghyeop;Son, Hyeongseok;Lee, Junyong;Yoon, Haeun;Cho, Sunghyun;Lee, Seungyong
    • Journal of the Korea Computer Graphics Society
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    • v.26 no.3
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    • pp.61-68
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    • 2020
  • In this paper, we propose a deep learning framework for predicting a depth map of a 360° panorama image. Previous works use synthetic 360° panorama datasets to train networks due to the lack of realistic datasets. However, the synthetic nature of the datasets induces features extracted by the networks to differ from those of real 360° panorama images, which inevitably leads previous methods to fail in depth prediction of real 360° panorama images. To address this gap, we use domain adaptation to learn features shared by real and synthetic panorama images. Experimental results show that our approach can greatly improve the accuracy of depth estimation on real panorama images while achieving the state-of-the-art performance on synthetic images.

Omnidirectional Environmental Projection Mapping with Single Projector and Single Spherical Mirror (단일 프로젝터와 구형 거울을 활용한 전 방향프로젝션 시스템)

  • Kim, Bumki;Lee, Jungjin;Kim, Younghui;Jeong, Seunghwa;Noh, Junyong
    • Journal of the Korea Computer Graphics Society
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    • v.21 no.1
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    • pp.1-11
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    • 2015
  • Researchers have developed virtual reality environments to provide audience with more visually immersive experiences than previously possible. One of the most popular solutions to build the immersive VR space is a multi-projection technique. However, utilization of multiple projectors requires large spaces, expensive cost, and accurate geometry calibration among projectors. This paper presents a novel omnidirectional projection system with a single projector and a single spherical mirror.We newly designed the simple and intuitive calibration system to define the shape of environment and the relative position of mirror/projector. For successful image projection, our optimized omnidirectional image generation step solves image distortion produced by the spherical mirror and a calibration problem produced by unknown parameters such as the shape of environment and the relative position between the mirror and the projector. Additionally, the focus correction is performed to improve the quality of the projection. The experiment results show that our method can generate the optimized image given a normal panoramic image for omnidirectional projection in a rectangular space.

Proposal and Implementation of Intelligent Omni-directional Video Analysis System (지능형 전방위 영상 분석 시스템 제안 및 구현)

  • Jeon, So-Yeon;Heo, Jun-Hak;Park, Goo-Man
    • Journal of Broadcast Engineering
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    • v.22 no.6
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    • pp.850-853
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    • 2017
  • In this paper, we propose an image analysis system based on omnidirectional image and object tracking image display using super wide angle camera. In order to generate spherical images, the projection process of converting from two wide-angle images to the equirectangular panoramic image was performed and the spherical image was expressed by converting rectangular to spherical coordinate system. Object tracking was performed by selecting the desired object initially, and KCF(Kernelized Correlation Filter) algorithm was used so that robust object tracking can be performed even when the object's shape is changed. In the initial dialog, the file and mode are selected, and then the result is displayed in the new dialog. If the object tracking mode is selected, the ROI is set by dragging the desired area in the new window.