Natural scene-based vehicle body look-around camera self-calibration method and system based on a natural scene
A natural scene, self-calibration technology, applied in image data processing, instruments, 3D modeling, etc., can solve problems such as wrong results, long time consumption, and easy to find image feature points, and achieve high-precision results
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Embodiment 1
[0039] refer to Figure 1~3 The schematic diagram shows that this embodiment proposes a self-calibration method for the car body surround-view camera based on natural scenes. This method is based on the natural scene-based self-calibration method for the car body surround-view camera. It is mainly based on SLAM real-time positioning and mapping technology. Point information, combined with tools such as wheel odometer or GPS odometer, determines the trajectory of the camera movement, builds a global consistency map, and calculates the transformation matrix between adjacent cameras to complete the calibration of the surround-view camera. SLAM is the abbreviation of Synchronous Localization and Map Construction. SLAM is not so much an algorithm as it is a concept more appropriate. It is defined as solving the problem of "a robot starts from an unknown location in an unknown environment and passes repeated observations during the movement. Map features (such as wall corners, pilla...
Embodiment 2
[0101] refer to Figure 4~6 A self-calibration system for a car body surround-view camera based on a natural scene, characterized in that it includes an initial module 100, a camera odometer calibration module 200, a scene recovery module 300, a loopback detection module 400, a pose graph optimization module 500, and scene merging Module 600; where the initial module 100 is used to collect camera images and odometer data at each moment when the body is moving, and to obtain the initial pose and image internal feature point data of a single camera; the machine odometer calibration module 200 is used to calculate a single camera and the transformation matrix of the odometer; after the scene restoration module 300 is used to restore the coordinates of the scene point, the input loop detection module 400 is used to judge whether the vehicle has passed the historical position, that is, whether a loop occurs; the pose graph optimization module 500 is used to detect As a result, came...
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