Paper
17 March 2015 Assessing the influence of combinations of blockiness, blurriness, and packet loss impairments on visual attention deployment
Author Affiliations +
Proceedings Volume 9394, Human Vision and Electronic Imaging XX; 93940Z (2015) https://doi.org/10.1117/12.2083487
Event: SPIE/IS&T Electronic Imaging, 2015, San Francisco, California, United States
Abstract
In digital video systems, impairments introduced during the capture, coding/decoding processes, delivery and display might reduce the perceived quality of the visual content. Recent developments in the area of visual quality have focused on trying to incorporate aspects of gaze patterns into the design of visual quality metrics, mostly using the assumption that visual distortions appearing in less salient areas might be less visible and, therefore, less annoying. Most of these studies, however, have considered the presence of a single artifact (e.g. blockiness or blur) impairing the image. In practice, this is not the case, as multiple artifacts may overlap, and their combined appearance may be strong enough to deviate saliency from its natural pattern. In this work, our focus is on measuring the impact and the influence of combinations of artifacts on the video saliency. For this purpose, we tracked eye-movements of participants in a subjective quality assessment experiment during a free-viewing and a quality assessment tasks. Results show that the gaze locations change from pristine videos to impaired videos. These changes seem to be more related to the quality level and content of videos than to the specific combination of artifacts.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Alexandre F. Silva, Mylène C. Q. Farias, and Judith A. Redi "Assessing the influence of combinations of blockiness, blurriness, and packet loss impairments on visual attention deployment", Proc. SPIE 9394, Human Vision and Electronic Imaging XX, 93940Z (17 March 2015); https://doi.org/10.1117/12.2083487
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Cited by 7 scholarly publications.
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KEYWORDS
Video

Visualization

Micro unmanned aerial vehicles

Video compression

Image quality

Eye

Image compression

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