Consistent Filtering of Videos and Dense Light-Fields Without Optic-Flow

Simple item page
dc.contributor.authorShekhar, Sumiten_US
dc.contributor.authorSemmo, Amiren_US
dc.contributor.authorTrapp, Matthiasen_US
dc.contributor.authorTursun, Okanen_US
dc.contributor.authorPasewaldt, Sebastianen_US
dc.contributor.authorMyszkowski, Karolen_US
dc.contributor.authorDöllner, Jürgenen_US
dc.contributor.editorSchulz, Hans-Jörg and Teschner, Matthias and Wimmer, Michaelen_US
dc.date.accessioned2019-09-29T06:46:53Z
dc.date.available2019-09-29T06:46:53Z
dc.date.issued2019
dc.description.abstractA convenient post-production video processing approach is to apply image filters on a per-frame basis. This allows the flexibility of extending image filters-originally designed for still images-to videos. However, per-image filtering may lead to temporal inconsistencies perceived as unpleasant flickering artifacts, which is also the case for dense light-fields due to angular inconsistencies. In this work, we present a method for consistent filtering of videos and dense light-fields that addresses these problems. Our assumption is that inconsistencies-due to per-image filtering-are represented as noise across the image sequence. We thus perform denoising across the filtered image sequence and combine per-image filtered results with their denoised versions. At this, we use saliency based optimization weights to produce a consistent output while preserving the details simultaneously. To control the degree-of-consistency in the final output, we implemented our approach in an interactive real-time processing framework. Unlike state-of-the-art inconsistency removal techniques, our approach does not rely on optic-flow for enforcing coherence. Comparisons and a qualitative evaluation indicate that our method provides better results over state-of-the-art approaches for certain types of filters and applications.en_US
dc.description.sectionheadersImage and Video Processing
dc.description.seriesinformationVision, Modeling and Visualization
dc.identifier.doi10.2312/vmv.20191326
dc.identifier.isbn978-3-03868-098-7
dc.identifier.pages125-134
dc.identifier.urihttps://doi.org/10.2312/vmv.20191326
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vmv20191326
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectImage processing
dc.subjectComputational photography
dc.titleConsistent Filtering of Videos and Dense Light-Fields Without Optic-Flowen_US
Files
Original bundle
Now showing 1 - 5 of 6
Thumbnail Image
Name:
125-134.pdf
Size:
97.61 MB
Format:
Adobe Portable Document Format
Download
Thumbnail Image
Name:
vmv-1013-supplementary-document.pdf
Size:
16.32 MB
Format:
Adobe Portable Document Format
Download
No Thumbnail Available
Name:
vmv-1013-limitation.mp4
Size:
532.15 MB
Format:
Unknown data format
Download
No Thumbnail Available
Name:
vmv-1013-methodology.mp4
Size:
372.12 MB
Format:
Unknown data format
Download
No Thumbnail Available
Name:
vmv-1013-real-time-interaction.mp4
Size:
93.52 MB
Format:
Unknown data format
Download
Collections
VMV19