Method and system for reconstructing time-varying point cloud based on framework registration

Abstract

The invention relates to a method and a system for reconstructing a time-varying point cloud based on framework registration. The method comprises the following steps of: acquiring a time-varying point cloud sequence of a movement object, and dividing the point cloud sequence into a plurality of frames; extracting a curve framework in each frame of the point cloud sequence; establishing a corresponding relationship of framework junctions of the curve framework between two adjacent frames; according to the corresponding relationship of the framework junctions of the curve framework, registering a framework sequence; according to the registered framework sequence, calculating a consistent framework sequence; and according to the consistent framework sequence, extracting movement data, and registering and completing point cloud data according to the consistent framework sequence and the movement data. According to the method and the system for reconstructing the time-varying point cloud based on the framework registration, the extracted curve framework is adopted, the corresponding relationship of the framework junctions is established, the consistent framework sequence is obtained by calculation, and the point cloud data is registered and completed according to the consistent framework sequence and the movement data, so that a new point cloud is reconstructed. Without an accurate grid template, the method is higher in universality.

Description

【Technical field】 [0001] The invention relates to the field of computer graphics processing, in particular to a time-varying point cloud reconstruction method and system based on skeleton registration. 【Background technique】 [0002] In recent years, with the rapid development of 3D scanning technology, some new scanning technologies, such as structured light scanners, spatio-temporal multi-view stereo reconstruction systems based on multiple cameras shooting videos, and depth cameras have emerged, which can interactively scan real The surface information of the object makes it possible to capture the motion and deformation of the object. The motion data sequence of the object surface obtained from these devices is a time-varying point cloud. The time-varying point cloud records the motion information of the object with high precision: including motion data and high-precision shape surface data. [0003] However, there are the following problems in the time-varying point c...

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Problems solved by technology

[0003] However, there are the following problems in the time-varying point cloud: there are usually a lot of noise and peripheral lines in the data. Due to the self-occlusion phenomenon of the captured object itself, at each moment, the obtained data cannot completely reflect the surface geometric information of the entire model. There is a lack of data; the device only outputs the geometric information of the sampling points of each frame, but does not track the relative motion of the captured object, resulting in a lack of correspondence between the sampling points of adjacent frames

The method based on physical flow constraints cannot balance algorithm efficiency and reconstruction accuracy, and the reconstructed grid sequence is not consistent, which brings inconvenience to subsequent texture mapping, motion data compression, and grid sequence editing.

[0007] The above three different methods are all constrained to realize the reconstruction of the motion model in a special case, the versatility is not strong, and the calculation is complicated

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