%0 Conference Paper %1 9123096 %A Men, H. %A Hosu, V. %A Lin, H. %A Bruhn, A. %A Saupe, D. %B Proceedings of the International Conference on Quality of Multimedia Experience (QoMEX) %D 2020 %K 2020 A05 B04 from:leonkokkoliadis sfbtrr161 visus visus:bruhnas %P 1-6 %R 10.1109/QoMEX48832.2020.9123096 %T Visual Quality Assessment for Interpolated Slow-Motion Videos Based on a Novel Database %U https://ieeexplore.ieee.org/document/9123096/authors#authors %X Professional video editing tools can generate slow-motion video by interpolating frames from video recorded at astandard frame rate. Thereby the perceptual quality of such in-terpolated slow-motion videos strongly depends on the underlyinginterpolation techniques. We built a novel benchmark databasethat is specifically tailored for interpolated slow-motion videos(KoSMo-1k). It consists of 1,350 interpolated video sequences,from 30 different content sources, along with their subjectivequality ratings from up to ten subjective comparisons per videopair. Moreover, we evaluated the performance of twelve exist-ing full-reference (FR) image/video quality assessment (I/VQA)methods on the benchmark. In this way, we are able to show thatspecifically tailored quality assessment methods for interpolatedslow-motion videos are needed, since the evaluated methods –despite their good performance on real-time video databases – donot give satisfying results when it comes to frame interpolation.

@inproceedings{9123096, abstract = {Professional video editing tools can generate slow-motion video by interpolating frames from video recorded at astandard frame rate. Thereby the perceptual quality of such in-terpolated slow-motion videos strongly depends on the underlyinginterpolation techniques. We built a novel benchmark databasethat is specifically tailored for interpolated slow-motion videos(KoSMo-1k). It consists of 1,350 interpolated video sequences,from 30 different content sources, along with their subjectivequality ratings from up to ten subjective comparisons per videopair. Moreover, we evaluated the performance of twelve exist-ing full-reference (FR) image/video quality assessment (I/VQA)methods on the benchmark. In this way, we are able to show thatspecifically tailored quality assessment methods for interpolatedslow-motion videos are needed, since the evaluated methods –despite their good performance on real-time video databases – donot give satisfying results when it comes to frame interpolation.}, added-at = {2020-10-09T12:31:45.000+0200}, author = {Men, H. and Hosu, V. and Lin, H. and Bruhn, A. and Saupe, D.}, biburl = {https://puma.ub.uni-stuttgart.de/bibtex/29e2ba7ed4ac121e960caf0da5449f762/mueller}, booktitle = {Proceedings of the International Conference on Quality of Multimedia Experience (QoMEX)}, description = {Visual Quality Assessment for Interpolated Slow-Motion Videos Based on a Novel Database}, doi = {10.1109/QoMEX48832.2020.9123096}, interhash = {c0e0bb7000ad6ae8cdb7bed74fd448a5}, intrahash = {9e2ba7ed4ac121e960caf0da5449f762}, keywords = {2020 A05 B04 from:leonkokkoliadis sfbtrr161 visus visus:bruhnas}, pages = {1-6}, timestamp = {2020-10-09T10:31:45.000+0200}, title = {Visual Quality Assessment for Interpolated Slow-Motion Videos Based on a Novel Database}, url = {https://ieeexplore.ieee.org/document/9123096/authors#authors}, year = 2020 }