Abstract
Calibration of extrinsic parameters of the RGB-D camera can be applied in many fields, such as 3D scene reconstruction, robotics, and target detection. Many calibration methods employ a specific calibration object (i.e., a chessboard, cuboid, etc.) to calibrate the extrinsic parameters of the RGB-D color camera without using the depth map. As a result, it is difficult to simplify the calibration process, and the color sensor gets calibrated instead of the depth sensor. To this end, we propose a method that employs the depth map to perform extrinsic calibration automatically. In detail, the depth map is first transformed to a 3D point cloud in the camera coordinate system, and then the planes in the 3D point cloud are automatically detected using the Maximum Likelihood Estimation Sample Consensus (MLESAC) method. After that, according to the constraint relationship between the ground plane and the world coordinate system, all planes are traversed and screened until the ground plane is obtained. Finally, the extrinsic parameters are calculated using the spatial relationship between the ground plane and the camera coordinate system. The results show that the mean roll angle error of extrinsic parameter calibration was −1.14°. The mean pitch angle error was 4.57°, and the mean camera height error was 3.96 cm. The proposed method can accurately and automatically estimate the extrinsic parameters of a camera. Furthermore, after parallel optimization, it can achieve real-time performance for automatically estimating a robot’s attitude.
Highlights
RGB-D cameras, such as Kinect [1,2,3,4,5,6], PrimeSense, and Asus Xtion Pro, are traditional RGB cameras with added infrared cameras
The depth map is first transformed to a 3D point cloud in the camera coordinate system using internal parameters. en, the maximum likelihood estimation sample consensus (MLESAC) method [21] is used to extract the plane. e ergodic plane is iterated to obtain the extrinsic parameters
By using the automatic extrinsic parameter calibration method proposed in this study, the extrinsic parameters can be automatically corrected when there is no pedestrian, so as to solve the above problem
Summary
RGB-D cameras, such as Kinect [1,2,3,4,5,6], PrimeSense, and Asus Xtion Pro, are traditional RGB cameras with added infrared cameras. Is calibration method did not make full use of the depth information provided by the RGB-D camera, and the calibration results were essentially the extrinsic parameters of the color. Is method can directly use the color image calibration method, but it needs the extrinsic parameters of the color camera relative to the infrared camera and does not use the information provided by the depth map, so the process is complicated. (2) e second was to detect the features on the depth map provided by the infrared camera by designing a specific calibration object to obtain the extrinsic parameters of the camera based on the features (such as chessboard corners). Our proposed method, which we will call the ground plane calibration method, is based on the automatic calibration of the extrinsic parameters of a ground plane detection camera and belongs to the third category. Our proposed method, which we will call the ground plane calibration method, is based on the automatic calibration of the extrinsic parameters of a ground plane detection camera and belongs to the third category. is method can directly calibrate the infrared camera of an RGB-D camera using its depth information
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