Visual positioning method and system based on dense semantic three-dimensional map and mixed features

A visual positioning and three-dimensional map technology, applied in the field of visual positioning, can solve the problems of low robustness and accuracy, and achieve the effect of improving positioning accuracy and robustness

Inactive Publication Date: 2020-10-13
INST OF AUTOMATION CHINESE ACAD OF SCI
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Problems solved by technology

[0003] In order to solve the above-mentioned problems in the prior art, that is, in order to solve the problem of low robustness and low accuracy of the existing visual positioning method under large appearance ch

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  • Visual positioning method and system based on dense semantic three-dimensional map and mixed features
  • Visual positioning method and system based on dense semantic three-dimensional map and mixed features
  • Visual positioning method and system based on dense semantic three-dimensional map and mixed features

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Embodiment Construction

[0050] In order to make the purpose, technical solutions and advantages of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than Full examples. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0051]The application will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain related inventions, rather than to limit the invention. It should also be noted that, for the convenience of description, only the parts related to the related invention ...

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Abstract

The invention belongs to the field of visual positioning, particularly relates to a visual positioning method and system based on a dense semantic three-dimensional map and mixed features, and aims tosolve the problem that an existing visual positioning method is low in robustness and accuracy under large appearance changes or photographing condition changes. The method comprises the steps of obtaining a dense three-dimensional model and a dense semantic three-dimensional model of a target scene; obtaining a plurality of candidate retrieval images of a query image; obtaining a matching relationship among the query image, each candidate retrieval image and the dense three-dimensional model; and estimating a temporary pose based on the matching relationship, projecting all visible three-dimensional points with semantics to the query image, counting the number of consistent semantic tags of two-dimensional projection points on the three-dimensional points and the query image as a semantic consistency score, and obtaining final positioning information through a pose calculation method based on weight RANSAC. According to the invention, the robustness and accuracy of video positioningare improved.

Description

technical field [0001] The invention belongs to the field of visual positioning, and in particular relates to a visual positioning method and system based on dense semantic three-dimensional maps and mixed features. Background technique [0002] At present, visual localization methods can be mainly divided into three types, namely methods based on image retrieval, methods based on deep learning, and methods based on 3D models. Compared with the first two types of methods, the 3D model-based method can provide more accurate camera poses. Although traditional 3D model-based localization methods work well when the query and database images are shot in similar environments, they can be used in situations where the scene appearance varies greatly, such as when the query and database images are in different locations. These traditional positioning methods are often unable to accurately locate the query image. The main reason is that these methods need to obtain a large number of...

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Application Information

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IPC IPC(8): G06T17/00G06F16/583
CPCG06T17/00G06F16/583
Inventor 申抒含时天欣崔海楠朱灵杰
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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