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4DLFVD: A 4D Light Field Video Dataset

Published: 22 September 2021 Publication History

Abstract

We present a 4D Light Field (LF) video dataset, collected by a custom-made camera matrix, to be used for designing and testing algorithms and systems for LF video coding, processing, and streaming. Compared to existing LF datasets, ours provides LF videos, as opposed to only images, and at higher frame resolution, higher number of viewpoints, and/or higher framerate, offering the best visual quality LF video dataset. To achieve this, we built a 10 x 10 LF capture matrix composed of 100 cameras, each with a 1920 x 1056 resolution. We used this matrix to record videos in real and varying illumination and scene dynamics conditions. The dataset contains a total of nine groups of LF videos: eight groups collected with a fixed camera matrix position and orientation recording indoor potted plants, furniture, etc., and the last group collected by rotating around an outdoor environment with roadside vehicles, pedestrians, etc. Each group of LF videos consists of 100 video streams encoded with H.265/HEVC. Scene changes vary from static to slightly dynamic to highly dynamic, providing a good level of diversity. As an example, we present the results of a depth estimation method and show that our dataset can be used for applications such as objection detection, 3D modeling, and others.

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References

[1]
Stanford University Computer Graphics Laboratory. 2008. Light Field Datasets. http://lightfield.stanford.edu/lfs.html.
[2]
Donald G. Dansereau, Bernd Girod, and Gordon Wetzstein. 2019. LiFF: Light Field Features in Scale and Depth. In Computer Vision and Pattern Recognition (CVPR). IEEE. http://dgd.vision/Papers/dansereau2019liff.pdf
[3]
Laurent Guillo, Xiaoran Jiang, Gauthier Lafruit, and Christine Guillemot. 2018. Light field video dataset captured by a R8 Raytrix camera (with disparity maps). INTERNATIONAL ORGANISATION FOR STANDARDISATION ISO/IEC JTC1/SC29/WG1 and WG11 (2018).
[4]
Katrin Honauer, Ole Johannsen, Daniel Kondermann, and Bastian Goldluecke. 2016. A dataset and evaluation methodology for depth estimation on 4d light fields. In Asian Conference on Computer Vision. Springer, 19--34.
[5]
Li Li, Zhu Li, Bin Li, Dong Liu, and Houqiang Li. 2017. Pseudo-Sequence-Based 2-D Hierarchical Coding Structure for Light-Field Image Compression. IEEE Journal of Selected Topics in Signal Processing 11, 7 (2017), 1107--1119.
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G. Lafruit M.-L. Champel, R. Koenen and M. Budagavi. 2018. Draft 1.0 of ISO/IEC 23090-1: Technical Report on Architectures for Immersive Media. MPEG-I.
[7]
Massachusetts Institute of Technology Media Lab. 2013. MIT Synthetic Light Field Archives. https://web.media.mit.edu/ gordonw/SyntheticLightFields/index.php.
[8]
C. Perra and P. Assuncao. 2016. High efficiency coding of light field images based on tiling and pseudo-temporal data arrangement. In IEEE International Conference on Multimedia and Expo Workshops. 1--4.
[9]
Abhilash Sunder Raj, Michael Lowney, Raj Shah, and Gordon Wetzstein. 2016. Stanford lytro light field archive.
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Gengkun Wang, Wei Xiang, Mark Pickering, and Chang Wen Chen. 2016. Light field multi-view video coding with two-directional parallel inter-view prediction. IEEE Transactions on Image Processing 25, 11 (2016), 5104--5117.
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Ting-Chun Wang, Jun-Yan Zhu, Nima Khademi Kalantari, Alexei A Efros, and Ravi Ramamoorthi. 2017. Light field video capture using a learning-based hybrid imaging system. ACM Transactions on Graphics (TOG) 36, 4 (2017), 1--13.
[12]
Wei Xiang, Gengkun Wang, Mark Pickering, and Yongbing Zhang. 2016. Big video data for light-field-based 3D telemedicine. IEEE Network 30, 3 (2016), 30--38.
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Zhengyou Zhang. 2000. A flexible new technique for camera calibration. IEEE Transactions on pattern analysis and machine intelligence 22, 11 (2000), 1330--1334.

Cited By

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  • (2024)基于梯度下降深度均衡模型的动态光场重建(特邀)Laser & Optoelectronics Progress10.3788/LOP24140061:16(1611006)Online publication date: 2024
  • (2024)元光场事件计算成像(特邀)Laser & Optoelectronics Progress10.3788/LOP24138061:16(1611009)Online publication date: 2024
  • (2024)A Light-Field Video Dataset of Scenes with Moving Objects Captured with a Plenoptic Video CameraElectronics10.3390/electronics1311222313:11(2223)Online publication date: 6-Jun-2024
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cover image ACM Conferences
MMSys '21: Proceedings of the 12th ACM Multimedia Systems Conference
June 2021
254 pages
ISBN:9781450384346
DOI:10.1145/3458305
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 22 September 2021

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Author Tags

  1. camera matrix
  2. dataset
  3. depth estimation
  4. light field video

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  • Research-article

Funding Sources

  • 2020 PoC(Proof of Conception) Project of Zhongguancun Open Laboratory: 5G+AI based Six Degree of Freedom Light Field Collection and Display Technology for Archaeological and Cultural Preservation

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MMSys '21
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MMSys '21: 12th ACM Multimedia Systems Conference
September 28 - October 1, 2021
Istanbul, Turkey

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MMSys '21 Paper Acceptance Rate 18 of 55 submissions, 33%;
Overall Acceptance Rate 176 of 530 submissions, 33%

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Cited By

View all
  • (2024)基于梯度下降深度均衡模型的动态光场重建(特邀)Laser & Optoelectronics Progress10.3788/LOP24140061:16(1611006)Online publication date: 2024
  • (2024)元光场事件计算成像(特邀)Laser & Optoelectronics Progress10.3788/LOP24138061:16(1611009)Online publication date: 2024
  • (2024)A Light-Field Video Dataset of Scenes with Moving Objects Captured with a Plenoptic Video CameraElectronics10.3390/electronics1311222313:11(2223)Online publication date: 6-Jun-2024
  • (2024)Unsupervised Disparity Estimation for Light Field VideosICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)10.1109/ICASSP48485.2024.10446981(2620-2624)Online publication date: 14-Apr-2024
  • (2023)Space-Time Super-Resolution for Light Field VideosIEEE Transactions on Image Processing10.1109/TIP.2023.330012132(4785-4799)Online publication date: 1-Jan-2023
  • (2023)Edge-Assisted Virtual Viewpoint Generation for Immersive Light FieldIEEE MultiMedia10.1109/MMUL.2022.323277130:2(18-27)Online publication date: 1-Apr-2023
  • (2023)LiTrix: A Lightweight Live Light Field Video Scheme for Metaverse Stereoscopic ApplicationsIEEE Internet of Things Magazine10.1109/IOTM.001.22001886:2(137-142)Online publication date: Jun-2023
  • (2023)FEAMNet: Light Field Depth Estimation Network Based On Feature Extraction and Attention Mechanism2023 International Joint Conference on Neural Networks (IJCNN)10.1109/IJCNN54540.2023.10191959(1-8)Online publication date: 18-Jun-2023
  • (2023)CutMIB: Boosting Light Field Super-Resolution via Multi-View Image Blending2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52729.2023.00167(1672-1682)Online publication date: Jun-2023
  • (2023)A Tutorial on Immersive Video Delivery: From Omnidirectional Video to HolographyIEEE Communications Surveys & Tutorials10.1109/COMST.2023.326325225:2(1336-1375)Online publication date: 1-Apr-2023

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