Image scene segmentation and layering joint solution method based on component set sampling

A technology of scene segmentation and components, which is applied in the field of computer vision and image scene understanding, can solve the problem of not having a unified understanding of the entire scene, and achieve the effects of increasing three-dimensional understanding, improving non-human accuracy, and expanding the scope

Active Publication Date: 2013-06-26
BEIHANG UNIV
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[0004] The above research status shows that scholars in this field only pay attention to one aspect of the

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  • Image scene segmentation and layering joint solution method based on component set sampling
  • Image scene segmentation and layering joint solution method based on component set sampling
  • Image scene segmentation and layering joint solution method based on component set sampling

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Embodiment Construction

[0042] The present invention will be further described in detail below in conjunction with the accompanying drawings, so that those skilled in the art can implement it with reference to the description.

[0043] The invention provides an image scene segmentation and layering joint solution method based on component set sampling. This method can obtain the semantic category information of the image scene and the hierarchical relationship of the scene objects. The overall process is as follows: the input image is over-segmented to obtain the superpixels of the input image, wherein all pixels in each superpixel of the input image belong to the same semantic category and the same hierarchical category; training on the training data set obtains the semantic The discriminative model of category and the discriminative model of hierarchical category, and according to these two models, the probability value of each superpixel in the input image belonging to each semantic category and t...

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Abstract

The invention discloses an image scene segmentation and layering joint solution method based on component set sampling. The method comprises the following steps of: performing over-segmentation treatment on an input image to obtain a super-pixel set of the image; training on a training dataset to obtain a discriminant model of semantic category and a discriminant model of layer category, and obtain a probability value (of each super-pixel in the input image) belonging to each semantic category and a probability vale belonging to each layer category according to the two models; structuring a candidate graph structure of the input image and calculating a node weighted value, a positive side weighted value and a negative side weighted value; and based on the a candidate graph structure, obtaining an optimal solution by reasoning via a component set sampling algorithm, wherein the optimal solution includes the exact semantic category and the exact layer category of each super-pixel of the input image. The method disclosed by the invention can be widely used for semantic information and layer information labeling of computer visual systems of military, aviation, aerospace, monitoring and manufacturing, and the like.

Description

technical field [0001] The invention relates to the fields of computer vision and image scene understanding, in particular to an image scene segmentation and layering joint solution method based on component set sampling. Background technique [0002] The overall scene understanding is an important research issue in the field of computer vision, which covers the understanding of the three-dimensional world beyond the two-dimensional plane, that is, not only the recognition, segmentation, and semantic classification of the two-dimensional scene, but also the semantics in the scene. To understand the three-dimensional relationship between objects. Many scholars in the world are devoted to the research of this problem, including the research of image segmentation and semantic category, the research of scene plane orientation restoration and the research of scene depth information restoration. The research on these issues belongs to the research category of scene understanding,...

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Application Information

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IPC IPC(8): G06T7/00
Inventor 陈小武李青赵沁平宋亚斐刘怡
Owner BEIHANG UNIV
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