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Video retargeting from a full-resolution video to a lower resolution display will inevitably cause information loss. Content-aware video retargeting techniques have been studied to avoid critical visual information loss while resizing a video. Maintaining the spatio-temporal coherence of a retargeted video is very critical on visual quality. Camera motions(More)
Saliency detection is widely used to extract the regions of interest in images. Many saliency detection models have been proposed for videos in the uncompressed domain. However, videos are always stored in the compressed domain such as MPEG2, H.264, MPEG4 Visual, etc. In this study, we propose a video saliency detection model based on feature contrast in(More)
We conduct subjective tests to evaluate the performance of scalable video coding with different spatial-domain bit-allocation methods, visual attention models, and motion feature extractors in the literature. For spatial-domain bit allocation, we use the selective enhancement and quality layer assignment methods. For characterizing visual attention, we use(More)
In this paper, we propose a novel image retargeting algorithm based on the sensitivity-tuned visual significance map which is composed of a saliency map and a gradient map. We develop a new saliency detection model based on the human visual sensitivity and amplitude spectrum of image patches. We use a coherent normalization based fusion method to combine(More)
—We propose a fast mode decision algorithm to reduce the computational complexity of adaptive GOP structure (AGS) in the scalable extension of H.264/AVC. AGS can improve the coding efficiency of the scalable extension of H.264. It, however, needs to perform motion-compensated temporal filtering (MCTF) of all possible GOP sizes, leading to much higher(More)