research-article

Open access

Casual 3D photography

Authors:

Richard Szeliski,

Johannes KopfAuthors Info & Claims

ACM Transactions on Graphics (TOG), Volume 36, Issue 6

Article No.: 234, Pages 1 - 15

https://doi.org/10.1145/3130800.3130828

Published: 20 November 2017 Publication History

Abstract

We present an algorithm that enables casual 3D photography. Given a set of input photos captured with a hand-held cell phone or DSLR camera, our algorithm reconstructs a 3D photo, a central panoramic, textured, normal mapped, multi-layered geometric mesh representation. 3D photos can be stored compactly and are optimized for being rendered from viewpoints that are near the capture viewpoints. They can be rendered using a standard rasterization pipeline to produce perspective views with motion parallax. When viewed in VR, 3D photos provide geometrically consistent views for both eyes. Our geometric representation also allows interacting with the scene using 3D geometry-aware effects, such as adding new objects to the scene and artistic lighting effects.

Our 3D photo reconstruction algorithm starts with a standard structure from motion and multi-view stereo reconstruction of the scene. The dense stereo reconstruction is made robust to the imperfect capture conditions using a novel near envelope cost volume prior that discards erroneous near depth hypotheses. We propose a novel parallax-tolerant stitching algorithm that warps the depth maps into the central panorama and stitches two color-and-depth panoramas for the front and back scene surfaces. The two panoramas are fused into a single non-redundant, well-connected geometric mesh. We provide videos demonstrating users interactively viewing and manipulating our 3D photos.

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Cited By

Wang QPiao Y(2024)A Virtual View Acquisition Technique for Complex Scenes of Monocular Images Based on Layered Depth ImagesApplied Sciences10.3390/app14221055714:22(10557)Online publication date: 15-Nov-2024
https://doi.org/10.3390/app142210557
Chang YShi XDai M(2024)A Real-Time Viewpoint Rendering System Based on Multi-Plane Images and Neural Radiance FieldsProceedings of the International Conference on Computer Vision and Deep Learning10.1145/3653781.3653809(1-6)Online publication date: 19-Jan-2024
https://dl.acm.org/doi/10.1145/3653781.3653809
Huang XZhang QFeng YLi HWang Q(2024)LTM-NeRF: Embedding 3D Local Tone Mapping in HDR Neural Radiance FieldIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2024.344862046:12(10944-10959)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1109/TPAMI.2024.3448620
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Index Terms

Casual 3D photography
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
        Reconstruction
      2. Image and video acquisition
        Computational photography
  2. Computer graphics
    1. Image manipulation
      1. Image-based rendering

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cover image ACM Transactions on Graphics

ACM Transactions on Graphics Volume 36, Issue 6

December 2017

973 pages

ISSN:0730-0301

EISSN:1557-7368

DOI:10.1145/3130800

Editor:
Kavita Bala

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Publication History

Published: 20 November 2017

Published in TOG Volume 36, Issue 6

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Cited By

Wang QPiao Y(2024)A Virtual View Acquisition Technique for Complex Scenes of Monocular Images Based on Layered Depth ImagesApplied Sciences10.3390/app14221055714:22(10557)Online publication date: 15-Nov-2024
https://doi.org/10.3390/app142210557
Chang YShi XDai M(2024)A Real-Time Viewpoint Rendering System Based on Multi-Plane Images and Neural Radiance FieldsProceedings of the International Conference on Computer Vision and Deep Learning10.1145/3653781.3653809(1-6)Online publication date: 19-Jan-2024
https://dl.acm.org/doi/10.1145/3653781.3653809
Huang XZhang QFeng YLi HWang Q(2024)LTM-NeRF: Embedding 3D Local Tone Mapping in HDR Neural Radiance FieldIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2024.344862046:12(10944-10959)Online publication date: 1-Dec-2024
https://dl.acm.org/doi/10.1109/TPAMI.2024.3448620
Wang LFrisvad JBo Jensen MBigdeli S(2024)StereoDiffusion: Training-Free Stereo Image Generation Using Latent Diffusion Models2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)10.1109/CVPRW63382.2024.00737(7416-7425)Online publication date: 17-Jun-2024
https://doi.org/10.1109/CVPRW63382.2024.00737
Weber EHolynski AJampani VSaxena SSnavely NKar AKanazawa A(2024)NeRFiller: Completing Scenes via Generative 3D Inpainting2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01959(20731-20741)Online publication date: 16-Jun-2024
https://doi.org/10.1109/CVPR52733.2024.01959
Tanay TMaggioni M(2024)Global Latent Neural Rendering2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.01865(19723-19733)Online publication date: 16-Jun-2024
https://doi.org/10.1109/CVPR52733.2024.01865
Lee SYoon JHo Lee J(2024)Modeling Practical Multi-Center-of-Projection Using EllipsoidIEEE Access10.1109/ACCESS.2024.345150212(122328-122339)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3451502
Fang LFang L(2024)Plenoptic ReconstructionPlenoptic Imaging and Processing10.1007/978-981-97-6915-5_4(75-189)Online publication date: 16-Oct-2024
https://doi.org/10.1007/978-981-97-6915-5_4
Fang LFang L(2024)High-Resolution Plenoptic SensingPlenoptic Imaging and Processing10.1007/978-981-97-6915-5_3(37-73)Online publication date: 16-Oct-2024
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Chen RZhao JZhang FChalmers ARhee T(2024)Neural Radiance Fields for Dynamic View Synthesis Using Local Temporal PriorsComputational Visual Media10.1007/978-981-97-2095-8_5(74-90)Online publication date: 10-Apr-2024
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