English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Depth maps are needed by various graphics rendering and processingoperations. Depth map streaming is often necessary when such operations areperformed in a distributed system and it requires in most cases fast performingcompression, which is why video codecs are often used. Hardware implementationsof standard video codecs enable relatively high resolution and frameratecombinations, even on resource constrained devices, but unfortunately thoseimplementations do not currently support RGB+depth extensions. However, theycan be used for depth compression by first packing the depth maps into RGB orYUV frames. We investigate depth map compression using a combination of depthmap packing followed by encoding with a standard video codec. We show that theprecision at which depth maps are packed has a large and nontrivial impact onthe resulting error caused by the combination of the packing scheme and lossycompression when bitrate is constrained. Consequently, we propose a variableprecision packing scheme assisted by a neural network model that predicts theoptimal precision for each depth map given a bitrate constraint. We demonstratethat the model yields near optimal predictions and that it can be integratedinto a game engine with very low overhead using modern hardware.

Neural Network Assisted Depth Map Packing for Compression Using Standard Hardware Video Codecs