A Theory for Multiresolution Signal Decomposition: The Wavelet Representation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Perceptual quality metrics applied to still image compression
Signal Processing - Special issue on image and video quality metrics
Algorithms for Defining Visual Regions-of-Interest: Comparison with Eye Fixations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Digital Image Processing (3rd Edition)
Digital Image Processing (3rd Edition)
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
Is bottom-up attention useful for object recognition?
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Foveation scalable video coding with automatic fixation selection
IEEE Transactions on Image Processing
Automatic foveation for video compression using a neurobiological model of visual attention
IEEE Transactions on Image Processing
Hi-index | 0.00 |
In this paper we investigate the utilization of visual saliency maps for ROI-based video coding of video-telephony applications. Visually salient areas indicated in the saliency map are considered as ROIs. These areas are automatically detected using an algorithm for visual attention (VA) which builds on the bottom-up approach proposed by Itti et al. A top-down channel emulating the visual search for human faces performed by humans has been added, while orientation, intensity and color conspicuity maps are computed within a unified multi-resolution framework based on wavelet subband analysis. Priority encoding, for experimentation purposes, is utilized in a simple manner: Frame areas outside the priority regions are blurred using a smoothing filter and then passed to the video encoder. This leads to better compression of both Intra-coded (I) frames (more DCT coefficients are zeroed in the DCT-quantization step) and Inter coded (P, B) frames (lower prediction error). In more sophisticated approaches, priority encoding could be incorporated by varying the quality factor of the DCT quantization table. Extended experiments concerning both static images as well as low-quality video show the compression efficiency of the proposed method. The comparisons are made against standard JPEG and MPEG-1 encoding respectively.