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Pushing the Limits for View Prediction in Video Coding
Linköping University, Department of Electrical Engineering, Information Coding. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-5698-5983
2017 (English)In: PROCEEDINGS OF THE 12TH INTERNATIONAL JOINT CONFERENCE ON COMPUTER VISION, IMAGING AND COMPUTER GRAPHICS THEORY AND APPLICATIONS (VISIGRAPP 2017), VOL 4, SCITEPRESS , 2017, p. 68-76Conference paper, Published paper (Refereed)
Abstract [en]

More and more devices have depth sensors, making RGB+D video (colour+depth video) increasingly common. RGB+D video allows the use of depth image based rendering (DIBR) to render a given scene from different viewpoints, thus making it a useful asset in view prediction for 3D and free-viewpoint video coding. In this paper we evaluate a multitude of algorithms for scattered data interpolation, in order to optimize the performance of DIBR for video coding. This also includes novel contributions like a Kriging refinement step, an edge suppression step to suppress artifacts, and a scale-adaptive kernel. Our evaluation uses the depth extension of the Sintel datasets. Using ground-truth sequences is crucial for such an optimization, as it ensures that all errors and artifacts are caused by the prediction itself rather than noisy or erroneous data. We also present a comparison with the commonly used mesh-based projection.

Place, publisher, year, edition, pages
SCITEPRESS , 2017. p. 68-76
Keywords [en]
Projection Algorithms; Video Coding; Motion Estimation
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-151812DOI: 10.5220/0006131500680076ISI: 000444907000007ISBN: 978-989-758-225-7 (print)OAI: oai:DiVA.org:liu-151812DiVA, id: diva2:1253223
Conference
12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP)
Note

Funding Agencies|Ericsson Research; Swedish Research Council [2014-5928]

Available from: 2018-10-04 Created: 2018-10-04 Last updated: 2019-11-19
In thesis
1. Interpolation Techniques with Applications in Video Coding
Open this publication in new window or tab >>Interpolation Techniques with Applications in Video Coding
2019 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Recent years have seen the advent of RGB+D video (color+depth video), which enables new applications like free-viewpoint video, 3D and virtual reality. This is however achieved by adding additional data, thus increasing the bitrate. On the other hand, the added geometrical data can be used for more accurate frame prediction, thus decreasing bitrate. Modern encoders use previously decoded frames to predict other ones, meaning they only need to encode the difference. When geometrical data is available, previous frames can instead be projected to the frame that is currently predicted, thus reaching a higher accuracy and a higher compression.

In this thesis, different techniques are described and evaluated enabling such a prediction scheme based on projecting from depth-images, so called depth-image based rendering (DIBR). A DIBR method is found that maximizes image quality, in terms of minimizing the differences of the projected frame to the groundtruth of the frame it was projected to, i.e. the frame that is to be predicted. This was achieved by evaluating combinations of both state-of-the-art methods for DIBR as well as own extensions, meant to solve artifacts that were discovered during this work. Furthermore, a real-time version of this DIBR method is derived and, since the deph-maps will be compressed as well, the impact of depth-map compression on the achieved projection quality is evaluated, for different compression methods including novel extensions of existing methods. Finally, spline methods are derived for both geometrical and color interpolation.

Although all this was done with a focus on video compression, many of the presented methods are useful for other applications as well, like free-viewpoint video or animation.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2019. p. 38
Series
Linköping Studies in Science and Technology. Licentiate Thesis, ISSN 0280-7971 ; 1858
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-162116 (URN)9789179299514 (ISBN)
Presentation
2019-12-09, Ada Lovelace, Campus Valla, Linköping, 13:15 (English)
Opponent
Supervisors
Available from: 2019-11-19 Created: 2019-11-19 Last updated: 2019-12-10Bibliographically approved

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Ogniewski, JensForssén, Per-Erik
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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard1
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  • modern-language-association-8th-edition
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  • sv-SE
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Output format
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  • asciidoc
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