Abstract
In this paper, we describe an approach to saliency detection as a two-category (salient or not) soft clustering using topic model. In order to simulate human’s paralleled visual neural perception, many sub-regions are sampling from an image, where each one is considered as a set of colors from a codebook, which is a color palette for the image. We assume salient pixels would appear spatial adjacent more possibly, therefore in a same sub-region, while less salient pixels would either. Consequently, all the sub-regions are clustered into two assumed topics with probabilities: “salient”/“non-salient”, while “salient” one is decided to give saliency value of each pixel according to its posterior conditional probability. Our method will give a global saliency map with full resolution, and experiments illustrate it is competitive with the state-of-art methods.
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Jiang, G., Liu, X., Yue, J., Shi, Z. (2013). Exploit Spatial Relationships among Pixels for Saliency Region Detection Using Topic Model. In: Li, S., et al. Advances in Multimedia Modeling. MMM 2013. Lecture Notes in Computer Science, vol 7732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35725-1_16
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DOI: https://doi.org/10.1007/978-3-642-35725-1_16
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