%0 Conference Paper %1 conf/ldav/FriessLBFE18 %A Frieß, Florian %A Landwehr, Mathias %A Bruder, Valentin %A Frey, Steffen %A Ertl, Thomas %B Proceedings of the IEEE Symposium on Large Data Analysis and Visualization - Short Papers (LDAV) %D 2018 %I IEEE %K 2018 A02 INF from:leonkokkoliadis sfbtrr161 visus visus:brudervn visus:ertl visus:freysn visus:friessfn %P 87-91 %R 10.1109/LDAV.2018.8739215 %T Adaptive Encoder Settings for Interactive Remote Visualisation on High-Resolution Displays %U https://ieeexplore.ieee.org/document/8739215 %X We present an approach that dynamically adapts encoder settings for image tiles to yield the best possible quality for a given bandwidth. This reduces the overall size of the image while preserving details. Our application determines the encoding settings in two steps. In the first step, we predict the quality and size of the tiles for different encoding settings using a convolutional neural network. In the second step, we assign the optimal encoder setting to each tile, so that the overall size of the image is lower than a predetermined threshold. Commonly, for tiles that contain complicated structures, a high quality setting is used in order to prevent major information loss, while quality settings are lowered for others to keep the size below the threshold. We demonstrate that we can reduce the overall size of the image while preserving the details in areas of interest using the example of both particle and volume visualisation applications. %@ 978-1-5386-6873-3

@inproceedings{conf/ldav/FriessLBFE18, abstract = {We present an approach that dynamically adapts encoder settings for image tiles to yield the best possible quality for a given bandwidth. This reduces the overall size of the image while preserving details. Our application determines the encoding settings in two steps. In the first step, we predict the quality and size of the tiles for different encoding settings using a convolutional neural network. In the second step, we assign the optimal encoder setting to each tile, so that the overall size of the image is lower than a predetermined threshold. Commonly, for tiles that contain complicated structures, a high quality setting is used in order to prevent major information loss, while quality settings are lowered for others to keep the size below the threshold. We demonstrate that we can reduce the overall size of the image while preserving the details in areas of interest using the example of both particle and volume visualisation applications.}, added-at = {2020-10-09T12:31:46.000+0200}, author = {Frieß, Florian and Landwehr, Mathias and Bruder, Valentin and Frey, Steffen and Ertl, Thomas}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2cd94172a8697c000385aef6fd5193f3d/mueller}, booktitle = {Proceedings of the IEEE Symposium on Large Data Analysis and Visualization - Short Papers (LDAV)}, description = {Adaptive Encoder Settings for Interactive Remote Visualisation on High-Resolution Displays}, doi = {10.1109/LDAV.2018.8739215}, ee = {https://doi.org/10.1109/LDAV.2018.8739215}, interhash = {63dd0c0009c1d54897641c78c37cdc3e}, intrahash = {cd94172a8697c000385aef6fd5193f3d}, isbn = {978-1-5386-6873-3}, keywords = {2018 A02 INF from:leonkokkoliadis sfbtrr161 visus visus:brudervn visus:ertl visus:freysn visus:friessfn}, pages = {87-91}, publisher = {IEEE}, timestamp = {2020-10-09T10:31:46.000+0200}, title = {Adaptive Encoder Settings for Interactive Remote Visualisation on High-Resolution Displays}, url = {https://ieeexplore.ieee.org/document/8739215}, year = 2018 }