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A three-dimensional reconstruction method based on point cloud optimization sampling

A 3D reconstruction and point cloud technology, applied in the field of computer vision graphics, can solve the problems of high calculation cost, disparity map stripes, and only retaining, etc., to improve the calculation speed, avoid the stripe phenomenon, and shorten the optimization range.

Inactive Publication Date: 2019-06-18
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0005] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a 3D reconstruction method based on point cloud optimal sampling, the purpose of which is to solve the problem of large calculation cost and the disparity map obtained by matching in the traditional dynamic programming-based global stereo matching algorithm. There is a problem of stripes, and at the same time solve the problem of how to remove the smooth area to retain the main texture information in the reconstruction process, and how to retain only the accurate and necessary point cloud information in the multi-view fusion process

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  • A three-dimensional reconstruction method based on point cloud optimization sampling
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[0044] In order to make the purpose, technical solution and advantages of the present invention more clear, the specific implementation of the present invention will be further described below in conjunction with the accompanying drawings, but the method of the present invention is not limited.

[0045] The greatest contribution of the method of the present invention lies in the formation of a set of efficient 3D reconstruction process through the improved two-way DP algorithm, self-adaptive sampling, depth value estimation and sorting, etc., while extracting the main texture features, the redundant information is obviously reduced, and the The speed of reconstruction is improved, which has great significance in the field of three-dimensional reconstruction.

[0046] The flow of the method of the present invention can be divided into three sub-modules, distortion correction is performed on images collected by multiple cameras at the same time, stereo matching is performed on th...

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Abstract

The invention discloses a three-dimensional reconstruction method based on point cloud optimization sampling and belongs to the field of computer vision. The objective of the invention is to solve theproblem that in the three-dimensional reconstruction process of dense point cloud, under the condition that the main texture characteristics are ensured, the reconstruction speed is low. According tothe method, a mean shift algorithm is mainly utilized to carry out region segmentation on a plurality of corrected images; an improved bidirectional DP algorithm is adopted; sequentially carrying outstereo matching on the same regions after the adjacent images are segmented to obtain a disparity map; secondly, eliminating interference noise of the disparity map by using bilateral filtering to obtain a plurality of dense depth point cloud maps, then obtaining main texture features through self-adaptive random sampling, removing smooth areas, finally calculating depth value estimation of eachpoint cloud, and extracting the main point cloud according to the sequence of the estimation values. According to the method provided by the invention, more obvious texture features can be obtained ata higher calculation speed, and the method has a wide application prospect in natural scene three-dimensional reconstruction.

Description

technical field [0001] The present invention relates to the field of computer vision graphics, and more specifically, to a three-dimensional reconstruction method based on point cloud optimal sampling. Background technique [0002] In visual 3D reconstruction, stereo matching is the core link, which can be divided into local matching algorithm and global matching algorithm. Since the global matching algorithm uses the conditions of global constraints, the local area of ​​the image is not blurred, so the global stereo matching algorithm is commonly used in 3D reconstruction. The commonly used global stereo matching algorithms include graph cut (GC), belief propagation, and dynamic programming ( DP) and so on. The traditional dynamic programming algorithm uses the global energy minimum solution to divide a large decision-making problem into several sub-problems, so as to obtain the optimal disparity map. The stereo matching algorithm based on traditional dynamic programming ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T17/00G06T7/80G06T7/50G06T7/40G06T7/30G06T7/11G06T5/50G06T5/00
Inventor 宫大为何志恒叶小龙葛森刘洋
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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