Social image quality

Qiu, Guoping and Kheiri, Ahmed ORCID: https://orcid.org/0000-0002-6716-2130 2011. Social image quality. Presented at: Image Quality and System Performance VIII, San Francisco Airport, California, USA, 23 January 2011. Proc. SPIE 7867, Image Quality and System Performance VIII. , vol.7867 Society of Photo-optical Instrumentation Engineers, 78670S. 10.1117/12.872378

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Abstract

Current subjective image quality assessments have been developed in the laboratory environments, under controlledconditions, and are dependent on the participation of limited numbers of observers. In this research, with the help of Web 2.0 and social media technology, a new method for building a subjective image quality metric has been developed where the observers are the Internet users. A website with a simple user interface that enables Internet users from anywhere at any time to vote for a better quality version of a pair of the same image has been constructed. Users' votes are recorded and used to rank the images according to their perceived visual qualities. We have developed three rank aggregation algorithms to process the recorded pair comparison data, the first uses a naive approach, the second employs a Condorcet method, and the third uses the Dykstra's extension of Bradley-Terry method. The website has been collecting data for about three months and has accumulated over 10,000 votes at the time of writing this paper. Results show that the Internet and its allied technologies such as crowdsourcing offer a promising new paradigm for image and video quality assessment where hundreds of thousands of Internet users can contribute to building more robust image quality metrics. We have made Internet user generated social image quality (SIQ) data of a public image database available online (http://www.hdri.cs.nott.ac.uk/siq/) to provide the image quality research community with a new source of ground truth data. The website continues to collect votes and will include more public image databases and will also be extended to include videos to collect social video quality (SVQ) data. All data will be public available on the website in due course.

Item Type:	Conference or Workshop Item (Paper)
Status:	Published
Schools:	Mathematics
Subjects:	Q Science > QA Mathematics > QA76 Computer software
Publisher:	Society of Photo-optical Instrumentation Engineers
ISSN:	0277-786X
Last Modified:	31 Oct 2022 10:41
URI:	https://orca.cardiff.ac.uk/id/eprint/85725

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