Cross-modal image saliency detection method

A detection method and multi-modal image technology, applied in the field of computer vision, can solve problems such as inability to fuse multi-modal information together, modal noise or error, etc., achieve good multi-modal image saliency detection effect, increase robustness Stickiness, the effect of solving heterogeneity problems

Active Publication Date: 2018-11-27
ANHUI UNIVERSITY
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Problems solved by technology

[0005] The technical problem to be solved by the present invention is: the existing technology is easy to introduce modal noise or error, so that the multi-modal information cannot be well fused together, and a cross-modal image saliency detection method is provided

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[0042] The embodiments of the present invention are described in detail below. This embodiment is implemented on the premise of the technical solution of the present invention, and detailed implementation methods and specific operating procedures are provided, but the protection scope of the present invention is not limited to the following implementation example.

[0043] Such as figure 1As shown, this embodiment includes the following steps:

[0044] (1) Input paired multi-modal images, and use a superpixel segmentation algorithm to segment different modalities to obtain uniform and similarly sized superpixel regions;

[0045] (2) Design a multimodal image saliency detection model based on the graph manifold sorting algorithm, and introduce cross-modal soft consistency constraints and manifold sorting fit item sparsity constraints;

[0046] (3) Using the superpixels on the four sides of the image as the seed node, calculate the similarity between other nodes and the seed n...

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Abstract

The invention discloses a cross-modal image saliency detection method. The paired multi-modal images are inputted and different modes are divided by a super-pixel segmentation algorithm so as to obtain uniform super-pixel regions with approximate size; a multimodal image saliency detection model based on the graph manifold sorting algorithm is designed, and the cross-modal soft consistency constraint and the manifold sorting fitting term sparsity constraint are introduced; the super-pixels on four sides of the image are used as seed nodes and the similarity between other nodes and seed nodes is calculated so as to obtain a preliminary saliency map; referring to the foreground points obtained in the previous stage as the seed nodes and the similarity of other nodes to the node is calculated, and the final saliency map is obtained. A method for complementarily fusing the multimodal images based on the graph manifold sorting algorithm is provided, and l1 norm is introduced to realize cross-modal soft consistency constraint and the manifold sorting function fitting term sparsity constraint, i.e. partial inconsistency is allowed on the basis of coordination of multiple modes, and the robustness of the fitting term is increased.

Description

technical field [0001] The invention relates to a computer vision technology, in particular to a cross-modal image saliency detection method. Background technique [0002] Saliency detection based on manifold sorting is based on background nodes and foreground nodes, and an image saliency detection algorithm is proposed. Firstly, the salient image based on the background node set is calculated by using the background node as prior knowledge, combined with the image color features and positional relationship, because the background node is determined, according to the contrast relationship between the image superpixel and the background node, the foreground object can be superimposed The pixels are well highlighted, but the suppression of background noise is insufficient, and then the foreground is used as prior knowledge, and the saliency image based on the foreground node set calculated by using the image color features and position relationship can suppress the background ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/32G06K9/46
CPCG06V10/255G06V10/56
Inventor 李成龙夏威涂铮铮汤进罗斌
Owner ANHUI UNIVERSITY
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