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A Method for Automatic Image Segmentation and Semantic Annotation Based on Shape Vision Knowledge Base

A semantic annotation and automatic segmentation technology, applied in the field of image recognition, can solve the problems of no clean available shape visual knowledge base, no automatic segmentation and semantic annotation methods for unknown shapes, etc.

Active Publication Date: 2019-04-19
SHANDONG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0007] It can be seen that in the prior art, there is no clean and available shape visual knowledge base based on partial semantic information for everyone to use, and there is no automatic segmentation and semantic annotation method for unknown shapes.

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  • A Method for Automatic Image Segmentation and Semantic Annotation Based on Shape Vision Knowledge Base
  • A Method for Automatic Image Segmentation and Semantic Annotation Based on Shape Vision Knowledge Base
  • A Method for Automatic Image Segmentation and Semantic Annotation Based on Shape Vision Knowledge Base

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Embodiment Construction

[0079] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0080]On the one hand, the present invention constructs a fine-grained shape visual knowledge base, and on the other hand, automatically performs segmentation and semantic annotation on unknown shapes through the constructed fine-grained shape visual knowledge base. Different from traditional knowledge bases, this method not only provides coarse-grained shape information and semantic annotations, such as elephant, horse, cup, etc. At the same time, it also provides more fine-grained shape information and partial semantic annotations of object parts, such as head, nose, tail, etc., as well as the hierarchical semantic relationship between various parts. At the same time, all semantic annotations are based on WordNet and are not defined arbitrarily, so these annotations are relatively clean and reliable. This method also provides a method of knowledge tr...

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Abstract

The invention discloses an image automatic segmentation and semantic annotation method based on a shape vision knowledge base. The specific steps include: constructing a basic shape vision knowledge base; obtaining semantic statistical information related to the shape vision knowledge base; obtaining a secant line candidate set of an unknown shape ; Obtain the category candidate set and label candidate set of unknown shape; use integer linear programming to solve the optimal segmentation, semantic annotation of shape and partial semantic annotation. The invention constructs a shape vision knowledge base with a finer granularity compared to the existing knowledge base, and at the same time, can automatically segment and semantically annotate unknown shapes through the shape vision knowledge base, and has high scalability.

Description

technical field [0001] The invention belongs to the technical field of image recognition, in particular to an image automatic segmentation and semantic annotation method based on a shape vision knowledge base. Background technique [0002] With the development of the Internet and mobile Internet, there are more and more various pictures uploaded by users on the Internet. Image sharing platforms like Flickr, a photo sharing website owned by Yahoo, have long expected to convert digital images beyond existing image databases into billions of rich online image resources. It is possible to organize and understand images; at the same time, a large number of images on the Internet have prompted more and more researchers to study how to organize and organize these images in a semantic way and to explore and mine the visual aspects of these images. Knowledge. [0003] The above-mentioned research process on image recognition is long, and significant breakthroughs and progress have ...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06K9/46G06K9/34
CPCG06V10/267G06V10/752G06V10/44G06F18/40G06F18/22G06F18/24G06F18/214
Inventor 陈宝权王雅芳徐化永冯康吴炜
Owner SHANDONG UNIV