2014
DOI: 10.1117/12.2047850
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Audiovisual focus of attention and its application to Ultra High Definition video compression

Abstract: Using Focus of Attention (FoA) as a perceptual process in image and video compression belongs to well-known approaches to increase coding efficiency. It has been shown that foveated coding, when compression quality varies across the image according to region of interest, is more efficient than the alternative coding, when all region are compressed in a similar way. However, widespread use of such foveated compression has been prevented due to two main conflicting causes, namely, the complexity and the efficien… Show more

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Cited by 3 publications
(2 citation statements)
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“…However, when the gaze data is not available, visual attention models are used instead. Incorporating visual attention to increase coding efficiency has been done in the past [7], [8], [12], [14], and many previous works have proposed different ways to computationally model human visual attention [10], [11]. It should be mentioned that a comprehensive discussion or comparison between various saliency models is beyond the scope of this paper and readers can refer to [15]- [17], and [18] for such details.…”
Section: Related Workmentioning
confidence: 99%
“…However, when the gaze data is not available, visual attention models are used instead. Incorporating visual attention to increase coding efficiency has been done in the past [7], [8], [12], [14], and many previous works have proposed different ways to computationally model human visual attention [10], [11]. It should be mentioned that a comprehensive discussion or comparison between various saliency models is beyond the scope of this paper and readers can refer to [15]- [17], and [18] for such details.…”
Section: Related Workmentioning
confidence: 99%
“…The same premise that audiovisual events draw an observer's attention is the basis for their formulation. A similar approach is applied to high definition video compression in [36].…”
Section: Related Workmentioning
confidence: 99%