Subjective and objective quality assessment of Mobile Videos with In-Capture distortions
Deepti Ghadiyaram, Janice Pan, Alan C. Bovik, Anush K. Moorthy, Prasanjit Panda, Kai-Chieh Yang
Abstract
We designed and created a new video database that models a variety of complex distortions generated during the video capturing process on hand-held mobile capturing devices. We describe the content and characteristics of the new database, which we call the LIVE Mobile In-Capture Video Quality Database. It comprises a total of 208 videos that were captured using eight different smart-phones and were affected by six common in-capture distortions. We also conducted a subjective video quality assessment study using this data, wherein each video was assessed by 36 unique subjects. We evaluated several top-performing No-Reference IQA and VQA algorithms on the new database and find insights on how real-world in-capture distortions challenge both human subjects as well as automatic perceptual quality prediction models.
BibTeX
@inproceedings{icassp2017_subjectiveandobj,
title = {Subjective and objective quality assessment of Mobile Videos with In-Capture distortions},
author = {Deepti Ghadiyaram and Janice Pan and Alan C. Bovik and Anush K. Moorthy and Prasanjit Panda and Kai-Chieh Yang},
booktitle = {ICASSP 2017},
year = {2017}
}