• Title/Summary/Keyword: Dense Correspondences

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Three-Dimensional Reconselction using the Dense Correspondences from Sequence Images (연속된 영상으로부터 조밀한 대응점을 이용한 3차원 재구성)

  • Seo Yung-Ho;Kim Sang-Hoon;Choi Jong-Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.30 no.8C
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    • pp.775-782
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    • 2005
  • In case of 3D reconstruction from dense data in uncalibrated sequence images, we encounter with the problem for searching many correspondences and the computational costs. In this paper, we propose a key frame selection method from uncalibrated images and the effective 3D reconstruction method using the key frames. Namely, it can be performed on smaller number of views in the image sequence. We extract correspondences from selected key frames in image sequences. From the extracted correspondences, camera calibration process will be done. We use the edge image to fed dense correspondences between selected key frames. The method we propose to find dense correspondences can be used for recovering the 3D structure of the scene more efficiently.

Transformer-based dense 3D reconstruction from RGB images (RGB 이미지에서 트랜스포머 기반 고밀도 3D 재구성)

  • Xu, Jiajia;Gao, Rui;Wen, Mingyun;Cho, Kyungeun
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.11a
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    • pp.646-647
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    • 2022
  • Multiview stereo (MVS) 3D reconstruction of a scene from images is a fundamental computer vision problem that has been thoroughly researched in recent times. Traditionally, MVS approaches create dense correspondences by constructing regularizations and hand-crafted similarity metrics. Although these techniques have achieved excellent results in the best Lambertian conditions, traditional MVS algorithms still contain a lot of artifacts. Therefore, in this study, we suggest using a transformer network to accelerate the MVS reconstruction. The network is based on a transformer model and can extract dense features with 3D consistency and global context, which are necessary to provide accurate matching for MVS.