Visual Attention in Quality Assessment

被引:99
作者
Engelke, Ulrich
Kaprykowsky, Hagen [1 ,3 ]
Zepernick, Hans-Jurgen [2 ]
Ndjiki-Nya, Patrick
机构
[1] German Res Ctr Artificial Intelligence, Kaiserslautern, Germany
[2] Blekinge Inst Technol, Perth, WA 6845, Australia
[3] IRCAM Ctr Pompidou, Paris, France
关键词
EYE-MOVEMENT; SALIENCY; MODEL; INFORMATION; SUPPRESSION; FEATURES; REGIONS; SEARCH; MOTION;
D O I
10.1109/MSP.2011.942473
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Perceptual quality metrics are widely deployed in image and video processing systems. These metrics aim to emulate the integral mechanisms of the human visual system (HVS) to correlate well with visual perception of quality. One integral property of the HVS is, however, often neglected: visual attention (VA) [1]. The essential mechanisms associated with VA consist mainly of higher cognitive processing, deployed to reduce the complexity of scene analysis. For this purpose, a subset of the visual information is selected by shifting the focus of attention across the visual scene to the most relevant objects. By neglecting VA, perceptual quality models inherently assume that all objects draw the attention of the viewer to the same degree. © 2011 IEEE.
引用
收藏
页码:50 / 59
页数:10
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