Vehicle-mounted 360-degree panorama mosaic method

Abstract

The invention discloses a vehicle-mounted 360-degree panorama mosaic method which includes utilizing a double-curve model to match a fisheye camera model, and calculating fisheye camera model parameters; confirming a mapping relation between a picture coordinate system and a camera coordinate system; confirming a homography matrix from the camera coordinate system to a ground coordinate system; generating a mapping lookup table from the picture coordinate system to the ground coordinate system; and enabling ground pictures obtained by a camera to be matched into a final aerial view according to the mapping lookup table. According to the vehicle-mounted 360-degree panorama matching method, for complexity of images of four view fields of the vehicle-mounted environment, the mapping lookup table from an original view field to the aerial view is built by utilizing the mapping relation. Compared with feature point match, the method only depends on the coordinate relation, a coordinate is relatively fixed when the camera is fixed, so compared with matching, the method is reliable. The original pictures are directly mapped to positions below the camera coordinate system, mapping from the camera coordinate system to a world coordinate system is omitted, errors are reduced, and accuracy is high.

Description

technical field [0001] The invention relates to the technical field of automotive electronics, in particular to a vehicle-mounted 360-degree panorama splicing method. Background technique [0002] The vehicle-mounted 360-degree surround-view splicing system is one of the subsystems that assist vehicle-mounted active safety. It is the basis for vehicle-mounted surround-view object recognition and ranging, and three-dimensional driving environment reconstruction. It is also a safety assistance system that increases the driving reliability of users, especially new drivers. one. At the same time, intelligent elements are added to the existing vehicle system to increase the driving experience. It is a design obtained by enhancing practicability and intuitiveness on the basis of active safety systems such as reversing radar and automatic parking system. The core of its algorithm implementation lies in the splicing and fusion of the bird's-eye view. The algorithm is mainly divide...

AI Technical Summary

Problems solved by technology

[0003] In the prior art, the patent application with the application number 201110199571.9 mainly uses shif feature point matching and RANSAC matching of the optimal stitching line to determine the stitching result. The disadvantage of this solution is that the extraction of shif feature points is very real-time and the environment is complex It is difficult to accurately determine the feature points in the vehicle-mounted surround view system, and the intersecting areas under the other four fields of view cannot guarantee enough feature points for matching, so this solution often fails to meet the requirements of real-time and accuracy; application number The patent application for 201110234021.6 mainly matches the Harris corners of the two images to achieve splicing. Although this method of finding corners is simple, it has low reliability, is sensitive to noise, and has poor robustness; the patent application number is 201010561115.X The application uses the rough calculation of the transfer vector of the down-sampled image to obtain the stitching effect. The transfer vector cannot express the mapping relationship of all fisheye cameras well. For the car surround view system, the available stitching effect cannot be achieved.

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