Fundamental matrix and homograph matrix estimation method and system based on GPU (Graphics Processing Unit) parallel speedup

Abstract

The invention discloses a fundamental matrix and homograph matrix estimation method and system based on GPU (Graphics Processing Unit) parallel speedup. The method is realized in the following steps that: for a plurality of images, on the basis of feature points, utilizing a matching algorithm to obtain the matching list of each image pair, wherein the matching list comprises the matching information of the feature points of the image pairs; due to the restriction of the capacity of a video memory, only selecting M image pairs each time to carry out parallel computation, and carrying out parallel random sampling on feature point matching pairs in the M image pairs; according to a sampling result, carrying out the parallel computation to obtain corresponding candidate fundamental matrixes or candidate homograph matrixes and a corresponding interior point number; then, in the plurality of candidate fundamental matrixes or candidate homograph matrixes which belong to the same image pair, obtaining and optimizing the candidate matrix with the largest interior point number to obtain the final fundamental matrix or homograph matrix. By use of the method, the calculation time of the fundamental matrix and the homograph matrix can be greatly shortened.

Description

technical field [0001] The invention belongs to the field of computer vision, and more specifically relates to a method and system for estimating fundamental matrix and homography matrix based on GPU parallel acceleration. Background technique [0002] Three-dimensional reconstruction is the key technology to establish virtual reality expressing the objective world in the computer. In recent years, 3D reconstruction has increasingly become a relatively popular subject. Among them, the reconstruction of disordered images has gradually become the focus of many people's attention. The most classic method for the reconstruction of disordered images is the incremental Structure from Motion (SfM). The process of the method mainly includes: extracting image feature points; establishing the matching relationship of feature points between image pairs; calculating the dual-view geometric relationship between images; and estimating sparse 3D point cloud and camera parameters according...

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Problems solved by technology

[0005] Aiming at the above defects or improvement needs of the prior art, the present invention provides a method and system for estimating fundamental matrix and homography matrix based on GPU parallel acceleration, thus solving the problems existing in existing fundamental matrix and homography matrix estimation methods. Time-consuming and inefficient technical issues

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