@inproceedings{a1ebb20a89894793ba6b9ebea5b95152,
title = "Spatiotemporal feature combination model for no-reference video quality assessment",
abstract = "One of the main challenges in no-reference video quality assessment is temporal variation in a video. Methods typically were designed and tested on videos with artificial distortions, without considering spatial and temporal variations simultaneously. We propose a no-reference spatiotemporal feature combination model which extracts spatiotemporal information from a video, and tested it on a database with authentic distortions. Comparing with other methods, our model gave satisfying performance for assessing the quality of natural videos.",
keywords = "feature combination, no-reference, spatiotemporal, video quality assessment",
author = "Hui Men and Hanhe Lin and Dietmar Saupe",
note = "Funding Information: ACKNOWLEDGMENT We thank the German Research Foundation (DFG) for financial support within project A05 of SFB/Transregio 161. Publisher Copyright: {\textcopyright} 2018 IEEE.; 10th International Conference on Quality of Multimedia Experience, QoMEX 2018 ; Conference date: 29-05-2018 Through 01-06-2018",
year = "2018",
month = sep,
day = "11",
doi = "10.1109/QoMEX.2018.8463426",
language = "English",
isbn = "978-1-5386-2606-1",
series = "2018 10th International Conference on Quality of Multimedia Experience, QoMEX 2018",
publisher = "IEEE",
booktitle = "2018 10th International Conference on Quality of Multimedia Experience (QoMEX 2018)",
}