Visual SLAM method based on semantic segmentation dynamic points

A semantic segmentation and dynamic point technology, applied in the field of computer vision, can solve problems such as inaccurate camera pose estimation, reduced robustness of visual odometry, and inability to build a globally consistent map, achieving the goal of improving accuracy and accuracy Effect
CN113516664APending Publication Date: 2021-10-19CHANGCHUN UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN ยท China
Current Assignee / Owner
CHANGCHUN UNIV OF TECH
Publication Date
2021-10-19

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Abstract

The invention discloses a visual SLAM method based on semantic segmentation dynamic points, and relates to the technical field of computer vision. The method comprises the following steps: acquiring environment image information through an RGB-D camera, and performing feature extraction and semantic segmentation on an obtained image to obtain an extracted ORB feature point and a semantic segmentation result; using a dynamic object detection algorithm based on multi-view geometric constraints to detect residual dynamic objects and reject dynamic feature points; and tracking, local mapping and loopback detection threads are executed in sequence, so that an accurate static scene octree three-dimensional semantic map is constructed in a dynamic scene, and finally the visual SLAM method based on semantic segmentation dynamic points facing the dynamic scene is realized.
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Description

Technical field:

[0001] The present invention relates to the technical field of computer vision, and more specifically, relates to a visual SLAM method based on semantically segmented dynamic points. Background technique:

[0002] Simultaneous localization and mapping (SLAM, simultaneous localization and mapping) research has a long history. It was first proposed by Smith et al., and then gradually improved by scholars. It refers to the fact that the robot estimates its own position through the information obtained by the mounted sensors when the environment is unknown, and at the same time constructs a map of the perceived surrounding environment. Visual SLAM is a system that uses cameras as sensors to complete positioning and mapping tasks. It is a prerequisite for mobile robots to complete intelligent tasks, and has become a hot spot in the current research on autonomous mobile navigation of robots.

[0003] At present, researchers have found many mature algorithms, such...

Claims

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