Three-dimensional map construction method and device, electronic equipment and storage medium

Abstract

The invention discloses a three-dimensional map construction method and device, electronic equipment and a storage medium. The three-dimensional map construction method comprises the following steps: acquiring at least one frame of image shot by a mobile camera device in a target area; performing semantic segmentation on each frame of image to obtain corresponding semantic segmentation information; performing pose estimation on each image according to the corresponding semantic segmentation information to obtain a pose estimation result; and constructing a three-dimensional map in combination with the semantic segmentation information and the pose estimation result corresponding to each frame of the image. According to the three-dimensional map construction method provided by the embodiment of the invention, a long-term vision SLAM method capable of effectively coping with the extreme appearance change of a scene is provided on the basis of the high-level cognitive information obtained by scene semantic segmentation; self-adaptive high-level cognition for a dynamic environment is formed through map representation fused with semantic information and updating and association of the map representation, and the active cognition ability of a robot system is improved.

Description

technical field [0001] The present application relates to the technical field of computer vision, and in particular to a method, device, electronic equipment and storage medium for constructing a three-dimensional map. Background technique [0002] Existing perception methods face the challenges of real dynamic scene applications with large time spans and large appearance changes, and there are limitations in robustness and long-term performance, making it difficult to detect dynamic objects under conditions such as dynamic objects, illumination changes, seasonal changes, and large viewing angle changes. Perceptual failure is easy to occur; semantic SLAM often only introduces semantic information into a certain link of SLAM, which can improve algorithm performance to a certain extent, but it is still not clear what role semantic information plays in SLAM, and how to make full use of it in each link of visual SLAM. , Reasonable and efficient use of semantic information; the r...

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Problems solved by technology

[0002] Existing perception methods face the challenges of real dynamic scene applications with large time spans and large appearance changes, and there are limitations in robustness and long-term performance, making it difficult to detect dynamic objects under conditions such as dynamic objects, illumination changes, seasonal changes, and large viewing angle changes. Perceptual failure is prone to occur; semantic SLAM often only introduces semantic information into a certain link...

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