Paper
10 February 2009 Subjective video quality assessment methods for recognition tasks
Carolyn G. Ford, Mark A. McFarland, Irena W. Stange
Author Affiliations +
Proceedings Volume 7240, Human Vision and Electronic Imaging XIV; 72400Z (2009) https://doi.org/10.1117/12.805371
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States
Abstract
To develop accurate objective measurements (models) for video quality assessment, subjective data is traditionally collected via human subject testing. The ITU has a series of Recommendations that address methodology for performing subjective tests in a rigorous manner. These methods are targeted at the entertainment application of video. However, video is often used for many applications outside of the entertainment sector, and generally this class of video is used to perform a specific task. Examples of these applications include security, public safety, remote command and control, and sign language. For these applications, video is used to recognize objects, people or events. The existing methods, developed to assess a person's perceptual opinion of quality, are not appropriate for task-based video. The Institute for Telecommunication Sciences, under a program from the Department of Homeland Security and the National Institute for Standards and Technology's Office of Law Enforcement, has developed a subjective test method to determine a person's ability to perform recognition tasks using video, thereby rating the quality according to the usefulness of the video quality within its application. This new method is presented, along with a discussion of two examples of subjective tests using this method.
© (2009) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Carolyn G. Ford, Mark A. McFarland, and Irena W. Stange "Subjective video quality assessment methods for recognition tasks", Proc. SPIE 7240, Human Vision and Electronic Imaging XIV, 72400Z (10 February 2009); https://doi.org/10.1117/12.805371
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Cited by 22 scholarly publications.
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KEYWORDS
Video

Video surveillance

Target recognition

Target detection

Video compression

Safety

Standards development

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