A 3D image registration method for AR system

A technology of 3D images and reference images, which is applied in image data processing, instruments, biological neural network models, etc., can solve the problems that the accuracy of 3D image registration cannot be guaranteed, so as to reduce training time, improve efficiency, ensure stability and The effect of precision
CN108460829BInactive Publication Date: 2019-05-24广州智能装备研究院有限公司
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
广州智能装备研究院有限公司
Publication Date
2019-05-24
Estimated Expiration
Not applicable · inactive patent

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Abstract

The invention discloses a three-dimensional image registration method for an AR system. The "estimation" of the best action of the reference image; the convolutional neural network training is performed on the sample image using a pyramid strategy, and two network models are generated for coarse alignment and fine alignment; the input scene image and the target image are used, and the key parameter model and The two network models perform coarse alignment and fine alignment respectively to complete 3D image registration. The present invention, based on the registration strategy of deep reinforcement learning, defines the three-dimensional image registration problem as a series of continuous actions to achieve image alignment and operation, and finds the best action in a limited solution to improve the alignment effect, which can ensure that The globally optimal alignment parameters ensure the accuracy of 3D image registration.
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Description

technical field

[0001] The invention relates to the field of augmented reality technology, in particular to a three-dimensional image registration method for an AR system. Background technique

[0002] In recent years, AR (Augmented Reality, Augmented Reality) technology has gradually become a research hotspot and has a very broad application prospect. In order to achieve the perfect fusion of virtual and reality, high-precision 3D image registration is very important.

[0003] Most of the traditional image registration algorithms are expressed as an optimization problem. A general matching strategy is used to measure the similarity between image pairs, and then the conversion parameters between images are calculated by the optimal criterion. This method faces two problems. Challenges, one is that the general matching strategy is usually non-convex in the registration parameter space, and the general optimal criterion does not perform well on this non-convex problem; the oth...

Claims

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