3D point cloud densification method and device based on binocular RGB image

A RGB image and point cloud technology, applied in the field of image processing, can solve problems such as not being able to complete object detection tasks in 3D space, lack of distance information in 2D image data, and a small number of laser beams, etc., to achieve good interpretability and improve Detection effect, the effect of obvious object features

CN111612728AActive Publication Date: 2020-09-01BEIJING JIAOTONG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Publication Date
2020-09-01

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Abstract

The embodiment of the invention provides a 3D point cloud densification method and device based on a binocular RGB image. The method comprises the following steps: step 1, generating a depth image from a binocular RGB image; estimating an approximate three-dimensional coordinate point of each pixel point of the depth image under a LiDAR coordinate system according to the depth information of the depth image; step 2, performing ground segmentation on the point cloud by using a cyclic RANSAC algorithm, and extracting a non-ground point cloud; step 3, inserting the extracted non-ground point cloud into a KDTree, searching a predetermined number of neighbor points in the KDTree according to the approximate three-dimensional coordinate points of each pixel point under the LiDAR coordinate system, and performing curved surface reconstruction by utilizing the neighbor points; and step 4, exporting accurate coordinate points of the approximate three-dimensional coordinate points by a computational geometry method according to a curved surface reconstruction result and calibration parameters of the LiDAR and the camera, and fusing the accurate coordinate points with the original LiDAR pointcloud to obtain a densified point cloud.
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Description

technical field

[0001] The present invention relates to the field of image processing, in particular to a 3D point cloud densification method and device based on binocular RGB images. Background technique

[0002] With the continuous development of technology, research in the field of driverless vehicles has also made great progress. In the field of unmanned vehicles, the detection and recognition of objects on the road ahead is one of its important tasks. LiDAR (Light Detection And Ranging) and cameras, as the two major sensors supporting object detection tasks, are essential in the configuration of unmanned vehicles.

[0003] LiDAR provides accurate three-dimensional distance information, so it is widely used. However, the cost of LiDAR increases as the number of emission wires increases, so the number of laser wires of LiDAR equipped on a vehicle is usually small, and the price of a Velodyne HDL-64E is about 4 times that of an ordinary family car, which makes self-drivi...

Examples

Embodiment Construction

[0028] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0029] In order to facilitate the understanding of the embodiments of the present invention, several specific embodiments will be taken as examples for further explanation below in conjunction with the accompanying drawings, and each embodiment does not constitute a limitation to the embodiments of the present invention.

[0030] Such as figure 1 As shown, it is a kind of 3D point cloud densification method based on binocular RGB image described in the present invention, comprising:

[0031] Step 1, generating a depth image from a binocula...