A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Principled Approach to Detecting Surprising Events in Video
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Video coding and delivery challenges for next generation IPTV
BT Technology Journal
A Visual Attention Based Region-of-Interest Determination Framework for Video Sequences*
IEICE - Transactions on Information and Systems
Visual sensitivity guided bit allocation for video coding
IEEE Transactions on Multimedia
ROI video coding based on H.263+ with robust skin-color detection technique
IEEE Transactions on Consumer Electronics
Automatic foveation for video compression using a neurobiological model of visual attention
IEEE Transactions on Image Processing
Fast algorithms for foveated video processing
IEEE Transactions on Circuits and Systems for Video Technology
A multicue Bayesian state estimator for gaze prediction in open signed video
IEEE Transactions on Multimedia
Making computers look the way we look: exploiting visual attention for image understanding
Proceedings of the international conference on Multimedia
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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.