TY - GEN
T1 - Datasheet for subjective and objective quality assessment datasets
AU - Barman, Nabajeet
AU - Reznik, Yuriy
AU - Martini, Maria
N1 - Note: Published in: Proceedings of the 2023 15th International Conference on Quality of Multimedia Experience (QoMEX). Ghent, Belgium : Institute of Electrical and Electronics Engineers, Inc. ISSN (online) 2472-7814 ISBN 9798350311730.
Organising Body: Ghent University, Norwegian University of Science and Technology, Interuniversity Microelectronics Centre
Organising Body: Ghent University, Norwegian University of Science and Technology, Interuniversity Microelectronics Centre
PY - 2023/6/20
Y1 - 2023/6/20
N2 - Over the years, many subjective and objective quality assessment datasets have been created and made available to the research community. However, there is no standard process for documenting the various aspects of the dataset, such as details about the source sequences, number of test subjects, test methodology, encoding settings, etc. Such information is often of great importance to the users of the dataset as it can help them get a quick understanding of the motivation and scope of the dataset. Without such a template, it is left to each reader to collate the information from the relevant publication or website, which is a tedious and time-consuming process. In some cases, the absence of a template to guide the documentation process can result in an unintentional omission of some important information. This paper addresses this simple but significant gap by proposing a datasheet template for documenting various aspects of sub-jective and objective quality assessment datasets for multimedia data. The contributions presented in this work aim to simplify the documentation process for existing and new datasets and improve their reproducibility. The proposed datasheet template is available on GitHub1, along with a few sample datasheets of a few open-source audiovisual subjective and objective datasets.
AB - Over the years, many subjective and objective quality assessment datasets have been created and made available to the research community. However, there is no standard process for documenting the various aspects of the dataset, such as details about the source sequences, number of test subjects, test methodology, encoding settings, etc. Such information is often of great importance to the users of the dataset as it can help them get a quick understanding of the motivation and scope of the dataset. Without such a template, it is left to each reader to collate the information from the relevant publication or website, which is a tedious and time-consuming process. In some cases, the absence of a template to guide the documentation process can result in an unintentional omission of some important information. This paper addresses this simple but significant gap by proposing a datasheet template for documenting various aspects of sub-jective and objective quality assessment datasets for multimedia data. The contributions presented in this work aim to simplify the documentation process for existing and new datasets and improve their reproducibility. The proposed datasheet template is available on GitHub1, along with a few sample datasheets of a few open-source audiovisual subjective and objective datasets.
KW - Computer science and informatics
KW - Databases
KW - Datasets
KW - Multimedia
KW - Objective Assessment
KW - Open-Source
KW - QoE
KW - Subjective Assessment
U2 - 10.1109/QoMEX58391.2023.10178546
DO - 10.1109/QoMEX58391.2023.10178546
M3 - Conference contribution
BT - Published in: Proceedings of the 2023 15th International Conference on Quality of Multimedia Experience (QoMEX). Ghent, Belgium : Institute of Electrical and Electronics Engineers, Inc. ISSN (online) 2472-7814 ISBN 9798350311730.
Organising Body: Ghent University, Norwegian University of Science and Technology, Interuniversity Microelectronics Centre
Organising Body: Ghent University, Norwegian University of Science and Technology, Interuniversity Microelectronics Centre
ER -