Multi-starting-point incremental three-dimensional reconstruction method based on large-scale disordered images

Abstract

The invention discloses a multi-starting-point incremental three-dimensional reconstruction method based on large-scale disordered images. The method comprises the steps of performing image matching, constructing a matching relationship chart, selecting a reconstruction starting point, detecting an edge, performing multi-starting-point three-dimensional reconstruction and splicing a submodel. By means of a clustering strategy and an iteration drift strategy, an image pair which is suitable as starting points is adaptively selected from a disordered image set and reconstruction is performed simultaneously; before reconstruction, determining an optimal reconstruction sub-process of each image according to a layered shortest path first algorithm, and determining a reconstruction boundary; and obtaining a whole three-dimensional reconstruction model according to sub-models obtained in different sub-processes and splicing the common parts contained in the sub-models. The three-dimensional reconstruction method according to the invention has advantages of settling a problem of suspension in reconstruction process when a current scene comprises a plurality of non-overlapped parts, obtaining a whole three-dimensional model which is covered by the image set, preventing three-dimensional structure error caused by matching and transmission of error images, realizing parallel processing in reconstruction sub-process, and improving image reconstruction efficiency.

Description

technical field [0001] The invention belongs to the technical field of computer vision, and in particular relates to a multi-start incremental three-dimensional reconstruction method based on large-scale disordered images. Background technique [0002] The 3D reconstruction based on computer vision technology can restore the 3D structure of the scene from the 2D image, which conforms to the habit of human beings to recognize the world, and has a wide application prospect. Using existing images on the Internet for 3D reconstruction can greatly simplify the steps of 3D reconstruction data collection, reduce the cost of data collection, and shorten the time of data collection. The parameters are unknown and the overlapping relationship of image scenes is unknown. [0003] The existing 3D scene reconstruction of a large-scale disordered image collection adopts the method of Structure from Motion (SFM), including four steps of image matching, initial image pair selection, increm...

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Problems solved by technology

[0005] In view of the above defects or improvement needs of the prior art, the present invention provides a multi-start point incremental 3D reconstruction method based on large-scale disordered images. Problems with Accuracy and Error Accumulation

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