Method of obtaining artificial scene main directions and image edges from multiple views

Abstract

The invention discloses a method of obtaining artificial scene main directions and image edges from multiple views. The method obtains three main directions which are mutually orthogonal in a plurality of artificial scene images, and finds edges corresponding to the main directions in the images. The method comprises the steps as follows: collecting feature points of the images, and performing calibration and reconstruction to generate point cloud through the feature points; calculating normal vector of the point cloud in the field and determining three main directions in a voting manner; then determining vanishing points in the images; and finally, extracting edges by combination with bilateral filtering. According to the invention, common structural information in the artificial scene can be accurately recovered, and can be represented completely and accurately in the images.

Description

Technical field [0001] The invention belongs to the fields of computer vision and computer graphics, and specifically relates to the fields of three-dimensional dense point cloud reconstruction, image edge extraction and large-scale optimization. Background technique [0002] In the field of computer vision, three-dimensional reconstruction has been the core issue for a long time, and great progress has been made in recent years. As a highly comprehensive engineering problem, 3D reconstruction involves all major research directions in the field of computer vision and graphics, including computational geometry, feature extraction, feature matching, regularization, surface reconstruction, and texture mapping. It itself It is also widely used in important fields such as geological and geomorphological research, three-dimensional maps, virtual reality, cultural relics protection, medical diagnosis, automatic navigation, and augmented reality. [0003] The commonly used 3D reconstructi...

AI Technical Summary

Problems solved by technology

Commonly used edge extraction algorithms (including Hough transform) cannot guarantee that the results meet the constraints of vanishing points, so further screening and clipping must be performed afterwards, which will make it difficult for edges to have both continuity and linearity, that is, when When the screening is stricter, only a lot of discontinuous short edges can be retained, but when the screening is looser, it cannot guarantee that the edge is a straight line consistent with the vanishing point

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