A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image and Video Compression Standards: Algorithms and Architectures
Image and Video Compression Standards: Algorithms and Architectures
Sparse bayesian learning and the relevance vector machine
The Journal of Machine Learning Research
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
Pulse discrete cosine transform for saliency-based visual attention
DEVLRN '09 Proceedings of the 2009 IEEE 8th International Conference on Development and Learning
IEEE Transactions on Image Processing
Visual attention guided bit allocation in video compression
Image and Vision Computing
Saliency Based on Multi-scale Ratio of Dissimilarity
ICPR '10 Proceedings of the 2010 20th International Conference on Pattern Recognition
A case-based reasoning approach for detection of salient regions in images
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
The H.264 Advanced Video Compression Standard
The H.264 Advanced Video Compression Standard
Saliency-based fidelity adaptation preprocessing for video coding
Journal of Computer Science and Technology - Special issue on natural language processing
Saliency-preserving video compression
ICME '11 Proceedings of the 2011 IEEE International Conference on Multimedia and Expo
Visual sensitivity guided bit allocation for video coding
IEEE Transactions on Multimedia
Automatic foveation for video compression using a neurobiological model of visual attention
IEEE Transactions on Image Processing
Information theory-based shot cut/fade detection and video summarization
IEEE Transactions on Circuits and Systems for Video Technology
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Recently Saliency maps from input images are used to detect interesting regions in images/videos and focus on processing these salient regions. This paper introduces a novel, macroblock level visual saliency guided video compression algorithm. This is modelled as a 2 step process viz. salient region detection and frame foveation. Visual saliency is modelled as a combination of low level, as well as high level features which become important at the higher-level visual cortex. A relevance vector machine is trained over 3 dimensional feature vectors pertaining to global, local and rarity measures of conspicuity, to yield probabilistic values which form the saliency map. These saliency values are used for non-uniform bit-allocation over video frames. To achieve these goals, we also propose a novel video compression architecture, incorporating saliency, to save tremendous amount of computation. This architecture is based on thresholding of mutual information between successive frames for flagging frames requiring re-computation of saliency, and use of motion vectors for propagation of saliency values.