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Multi-graph matching method based on low-rank tensor recovery

A graph matching and image technology, applied in graphics, data analysis in the genetic field, image field

Active Publication Date: 2019-11-12
NANJING UNIV OF POSTS & TELECOMM
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Simple pairwise matching is often not the best approach

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  • Multi-graph matching method based on low-rank tensor recovery
  • Multi-graph matching method based on low-rank tensor recovery
  • Multi-graph matching method based on low-rank tensor recovery

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[0079] Below in conjunction with accompanying drawing and specific embodiment, further illustrate the present invention, should be understood that these examples are only for illustrating the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various aspects of the present invention All modifications of the valence form fall within the scope defined by the appended claims of the present application.

[0080] A multi-graph matching method based on low-rank tensor recovery, the specific steps are as follows:

[0081] Step 1: Preprocess each frame image and perform feature extraction, that is, extract features of interest points and obtain location information of interest points.

[0082] SIFT (Scale Invariant Feature Transform) is often used to detect and describe local features in images. The description and detection of local image features can help identify objec...

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Abstract

The invention discloses a multi-graph matching method based on low-rank tensor recovery, and the method comprises the following steps: S1, carrying out the preprocessing of each frame of image, and carrying out the feature extraction, that is, extracting the features of interest points; S2, processing interest points of all frames of images, and extracting high-order information features of the interest points according to the topological relation of the interest points; S3, based on the multi-graph cyclic consistency, establishing a multi-graph high-order feature information tensor accordingto the global corresponding relationship between the replacement matrix and the image features; and S4, solving low-rank representation of the multi-image high-order feature information tensor based on an alternating direction multiplier method (ADMM) algorithm by adopting rank constraint as a standard, so that an optimal permutation matrix, namely a matching result matrix, corresponding to a plurality of images can be effectively calculated. According to the multi-graph matching method based on low-rank tensor recovery, graph matching consistency is achieved, matching precision is improved, and the multi-graph matching method has important significance in image matching application research, target recognition and target tracking technologies.

Description

technical field [0001] The invention relates to a multi-image matching method based on low-rank tensor recovery, which can be used in the field of image processing, especially data analysis in the fields of images, graphics, genes and the like. Background technique [0002] As a hot issue in pattern recognition and computer vision research, image matching originated from the research in the military field of the United States in the 1970s, and has received extensive attention and research. Image matching theory also plays a very important role in other research directions in the field of pattern recognition, such as image stitching technology, whose core is image matching; target tracking technology, which needs to rely on matching algorithms in the later stage; and for many detection and recognition algorithms, among which A large category is achieved by matching technology. It can be seen that image matching has very important century application value and theoretical res...

Claims

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Application Information

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IPC IPC(8): G06K9/46G06K9/62
CPCG06V10/44G06V10/751
Inventor 王雪琴朱虎李海波邓丽珍
Owner NANJING UNIV OF POSTS & TELECOMM
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