Monocular perception correction method and device based on sparse point cloud and storage medium

Abstract

The invention discloses a monocular perception correction method and device based on sparse point cloud, and a storage medium. The method comprises the steps of collecting the original camera data ofa monocular camera and the original sparse point cloud data of a radar sensor; processing the original camera data to obtain a three-dimensional detection result of a plurality of targets in an imageplane, the three-dimensional detection result comprising a target depth value and a two-dimensional bounding box; obtaining a conversion matrix; mapping the original sparse point cloud data to a corresponding position of an image plane based on the conversion matrix to obtain a point cloud projection depth map, setting a point cloud frame for each two-dimensional boundary frame in the point cloudprojection depth map, the point cloud projection depth map comprising a plurality of projection points corresponding to the original sparse point cloud data, and each projection point comprising a point cloud depth value; and correcting target depth values of a plurality of targets based on the point cloud depth values of the projection points contained in all the point cloud frames. The method isadvantaged in that by designing the point cloud frame characteristics, accuracy of correcting the target depth value is improved.

Description

technical field [0001] The present invention relates to the field of automatic driving, in particular to a monocular perception correction method, device and storage medium based on sparse point clouds. Background technique [0002] Intelligent perception is an important part of autonomous driving and the link between the vehicle and the environment. At present, mainstream sensing sensors include cameras, millimeter-wave radar, and lidar, etc., but multi-beam lidar is very expensive and not suitable for mass production, while the point clouds obtained by low-wire beam lidar and millimeter-wave radar are very sparse and not suitable for direct use. Do three-dimensional obstacle perception. Compared with binocular cameras, monocular cameras are relatively cheap sensors, and have unique advantages in obstacle detection and tracking. However, monocular cameras have limitations in depth information perception. [0003] In the prior art, the scheme of fusion of monocular camera ...

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Problems solved by technology

[0004] The purpose of the present invention is to provide a monocular perception method based on sparse point cloud, which is used to solve the problems of high algorithm complexity and large target depth estimation deviation when correcting the depth information of the monocular camera in the prior art

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