Visual Attention Model Based Regions of Interest Detection in Compressed Domain

As the reality that human beings usually pay more attention to areas of interest, visual attention model is a feasible method to find Regions of interest (ROIs) and measure the interest of a region. However, it is required to decompress image data completely. A visual attention model based ROIs detection in compressed domain is proposed in this paper, which can compute visual attention model with partially decompression. This method includes: (1) Visual saliency map computation; (2) Focus of attention (FOA) selection and shift; (3) ROIs detection. The experimental results show the proposed method performs well on the speed/accuracy of ROIs detection and interest measurement.