Laser radar 3D point cloud data combined camera self-calibrating method

A lidar, 3D point cloud technology, applied in image data processing, instrumentation, computing, etc., can solve the problems of poor self-calibration robustness, low accuracy, and complicated camera calibration operations.

Active Publication Date: 2018-05-01
BEIHANG UNIV
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Problems solved by technology

[0005] The invention discloses a camera self-calibration method combined with laser radar three-dimensional point cloud data, which solv

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  • Laser radar 3D point cloud data combined camera self-calibrating method
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  • Laser radar 3D point cloud data combined camera self-calibrating method

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Embodiment Construction

[0050] The present invention will be described in further detail below in conjunction with the accompanying drawings and specific embodiments.

[0051] The present invention provides a camera self-calibration method combined with laser radar three-dimensional point cloud data, based on the three-dimensional laser radar scanning and camera acquisition system for implementation of the scheme, the experimental equipment setup and schematic diagram of the scheme are as follows figure 1 As shown, the specific implementation flow chart is as follows figure 2 shown.

[0052] (1) LiDAR 3D point cloud and image data acquisition

[0053] First, fix the camera above the lidar and scan and shoot the same scene at the same time, the system schematic diagram is as follows image 3 As shown, it includes a CCD camera that can be disassembled at any time, and a two-dimensional laser radar integrated system. It mainly uses the vertical rotation of the rotating mirror to realize two-dimension...

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Abstract

The invention discloses a laser radar 3D point cloud data combined camera self-calibrating method, and relates to the technical fields of photography measurement and 3D reconstruction. 3D scanning iscarried out on a measured object, images of the same scene are collected in different viewpoints, features are extracted from the multiple collected images to obtain characteristic points, characteristic points in an overlapped area of any two images are searched for a corresponding nearest point, and a matching point pair is obtained by combining a random consistency algorithm; the matching pointpair is used to solve a fundamental matrix F so that the fundamental matrix F is not sensitive to Gaussian white noise; an objective function related to internal reference of a camera is establishedaccording to relation between the fundamental matrix and internal reference of the camera, and an optimization algorithm is used to solve the internal reference of the camera; and the internal reference, of the camera, needed by the optimization algorithm is set on the basis of laser radar 3D point cloud data, a pinhole imaging principle, a pixel size of a CCD camera and an image central position.Thus, the internal reference of the camera is calibrated accurately.

Description

technical field [0001] The invention relates to the field of photogrammetry and three-dimensional reconstruction, in particular to a camera self-calibration method combined with laser radar three-dimensional point cloud data. Background technique [0002] In the field of photogrammetry and 3D reconstruction, camera parameters are a necessary condition for restoring 2D images to 3D data, and their accuracy directly affects the restoration results. Therefore, how to calibrate the camera quickly, conveniently and accurately has always been a hot spot. Camera calibration is divided into three methods, which are traditional camera calibration, active vision calibration method and camera self-calibration method. Among them, traditional camera calibration requires high-precision calibration objects with known object shapes and sizes, and the calibration results obtained are high-precision, but the calibration process requires human intervention, complicated operations, and errors w...

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Application Information

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IPC IPC(8): G06T7/80
CPCG06T7/85
Inventor 李小路徐立军冯静刘畅
Owner BEIHANG UNIV
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