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Towards efficient context-specific video coding based on gaze-tracking analysis
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AI
DOI：10.1145/1314303.1314307.png)
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Abstract
En 中文
This article discusses a framework for model-based, context-dependent video coding based on exploitation of characteristics of the human visual system. The system utilizes variable-quality coding based on priority maps which are created using mostly context-dependent rules. The technique is demonstrated through two case studies of specific video context, namely open signed content and football sequences. Eye-tracking analysis is employed for identifying the characteristics of each context, which are subsequently exploited for coding purposes, either directly or through a gaze prediction model. The framework is shown to achieve a considerable improvement in coding efficiency.
Keywords:
algorithms
human factors
eye tracking
context-based video coding
subjective video quality
transformation of eye movements into useful knowledge
multimedia perceptual quality
applications
Journal
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6
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2.0K
Citations:
5.4K