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Spatial light clustering-based image surface feature point matching method

A feature point and clustering technology, applied in the field of computer vision, can solve the problems that traditional methods are difficult to have universal adaptability and the complexity of photogrammetry task conditions.

Active Publication Date: 2014-09-10
BEIJING INFORMATION SCI & TECH UNIV
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Problems solved by technology

[0006] From the above-mentioned traditional image surface feature point matching methods, the idea of ​​solving the problem is mostly located in the direct solution of the two-dimensional image surface space, that is, feature point matching is carried out on the image surface through constraints such as grayscale, features, and geometric relations. , but due to the complexity of the photogrammetry itself and the task conditions, it is difficult for the traditional method to have universal adaptability

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[0061] The objects and functions of the present invention and methods for achieving the objects and functions will be clarified by referring to the exemplary embodiments. However, the present invention is not limited to the exemplary embodiments disclosed below; it can be implemented in various forms. The essence of the description is only to help those skilled in the relevant art comprehensively understand the specific details of the present invention.

[0062] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar components, or the same or similar steps.

[0063] The invention mainly solves the imaging matching problem of common feature points.

[0064] The idea of ​​the present invention is based on the principle of the photogrammetry system: the source of the image plane information is the three-dimensional measured space, and the collinea...

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Abstract

The invention provides a spatial light clustering-based image surface feature point matching method. According to the spatial light clustering-based image surface feature point matching method, in a unique three-dimensional space, feature point matching is realized according to analysis on the clustering of image surface feature points corresponding to reconstruction light, and therefore, the uniqueness of a measured space is utilized to regress two-dimensional matching problems to a three-dimensional space so as to solve the problems. The spatial light clustering-based image surface feature point matching method includes the following steps of: (1) spatial light reconstruction; (2) light clustering threshold value determination; (3) light clustering judgment; and (4) image surface feature point matching; and (5) homonymy point merging.

Description

technical field [0001] The invention relates to the field of computer vision, in particular to a method for matching feature points of an image plane based on spatial light concentration. Background technique [0002] Feature point matching is a key step in computer vision, and has important applications in 3D reconstruction, motion estimation, image retrieval, camera calibration and other fields. In large-scale digital photogrammetry, feature point matching has an important impact on the accuracy, reliability, and automation of the measurement system. However, due to the change of shooting time, angle, environment, the use of multiple sensors and the defects of the sensor itself, the captured image is not only affected by noise, but also has serious grayscale distortion and geometric distortion. Under such conditions, how to achieve high accuracy, high matching accuracy, fast speed, robustness and strong anti-interference performance of matching algorithms has become the g...

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Application Information

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IPC IPC(8): G06T17/00G06T7/00
Inventor 王君董明利孙鹏燕必希娄小平
Owner BEIJING INFORMATION SCI & TECH UNIV
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