Texture fusion method for RGB-D camera real-time three-dimensional reconstruction

Abstract

The invention discloses a texture fusion method for RGB-D camera real-time three-dimensional reconstruction. The method includes: processing the RGB-D data stream to obtain the definition of a color image, selecting a key frame to extract a foreground, performing filtering and denoising on a depth image, calculating a normal vector of a depth image point cloud, and establishing a reconstructed data stream; quantitatively establishing an adaptive weight field of the color image in a mode of combining a probability method and a heuristic method, and taking the adaptive weight field as confidencecoefficient distribution of a real-time frame for describing color data; and by comparing the confidence coefficient weight in the adaptive weight field of the real-time frame with the latest confidence coefficient weight of the reference point cloud, selecting an operation from three operations of replacement, fusion and reservation to update a texture result, thereby realizing texture fusion applied to three-dimensional reconstruction. According to the method, high-quality data can be extracted, blurring of texture fusion can be effectively reduced, a clear texture reconstruction result isrealized, and the method is embedded into an RGB-D reconstruction framework with relatively low calculation cost, so that the texture reconstruction precision is remarkably improved.

Description

technical field [0001] The invention belongs to the field of computer vision and computer graphics image processing, and more specifically relates to a texture fusion method for real-time three-dimensional reconstruction of an RGB-D camera. Background technique [0002] With the increasing importance of 3D reconstruction technology in the fields of autonomous driving, virtual reality, robot positioning and navigation, how to use low-cost RGB-D sensors to obtain high-quality 3D reconstruction scenes in real time has become a hot issue. However, most of the current real-time 3D reconstruction based on RGB-D adopts the method of pixel-by-pixel weighted average sequence frame images to generate the texture of the object surface. This method is easy to destroy the structural information of the texture and cause the texture blur problem. [0003] At present, there are two main ways to improve the quality of texture reconstruction. The first way is to select high-quality data as m...

AI Technical Summary

Problems solved by technology

This method usually requires good initial reconstruction results, and at the same time requires high computing costs, it is difficult to realize real-time application on ordinary PCs or mobile terminals, and it is not easy to integrate into the existing three-dimensional reconstruction framework

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