Visual Attention Model Based Regions of Interest Detection in Compressed Domain

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Article Navigation > Chinese Journal of Electronics > 2012 > 21(4): 697-700

“Visual Attention Model Based Regions of Interest Detection in Compressed Domain,” Chinese Journal of Electronics, vol. 21, no. 4, pp. 697-700, 2012,

Citation:

“Visual Attention Model Based Regions of Interest Detection in Compressed Domain,” Chinese Journal of Electronics, vol. 21, no. 4, pp. 697-700, 2012,

“Visual Attention Model Based Regions of Interest Detection in Compressed Domain,” Chinese Journal of Electronics, vol. 21, no. 4, pp. 697-700, 2012,

Citation:

“Visual Attention Model Based Regions of Interest Detection in Compressed Domain,” Chinese Journal of Electronics, vol. 21, no. 4, pp. 697-700, 2012,

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Visual Attention Model Based Regions of Interest Detection in Compressed Domain

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Received Date: 2011-08-01
Rev Recd Date: 2012-02-01
Publish Date: 2012-10-25

Abstract

Abstract

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.

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References(10)

References

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