Multi-target collaborative salient-region detection method based on similarity propagation

Abstract

The invention discloses a multi-target collaborative salient-region detection method based on similarity propagation and relates to the field of multimedia information processing and computer vision. The method includes the following steps: with respect to a plurality of image files which are input, segmenting each image into superpixels and performing pairwise measurement on inter-superpixel similarities and establishing a superpixel similarity graph model; realizing inter-image superpixel similarity matrix bipartite matching through the superpixel similarity graph model; performing superpixel graph model similarity diffusion so as to obtain a similarity graph model; and calculating a saliency map through the similarity graph model. The method performs collaborative salience detection on a plurality of targets in a plurality of images which are input so that detection precision is improved; through a parallelization similarity propagation algorithm, the operation speed is reduced and needs in practical application are met; and experiment results show that the method obtains a more accurate detection result during a shorter calculation time.

Description

technical field [0001] The invention relates to the fields of multimedia information processing and computer vision, in particular to a multi-target cooperative salient region detection method based on similarity propagation, which can be used to detect the cooperative salientity of multiple targets in multiple images. Background technique [0002] At present, in the field of media computing, when solving problems such as collaborative saliency detection, by constructing a graph model, based on the similarity diffusion between nodes, and calculating the similarity response between superpixels in different images, the final Detection area. Simply put, co-saliency detection is a method used to detect common saliency between two images or multiple images. [0003] In the prior art, the final synergistic saliency result, ie, the saliency map, is usually generated by calculating the maximum response of superpixels in one image on another image on the result after similarity diff...

AI Technical Summary

Problems solved by technology

[0008] Finally, there are many inaccurate matches in the existing methods for the similarity matching of the graphical model between images

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