Pixel-Level Extrinsic Self Calibration of High Resolution LiDAR and Camera in Targetless Environments

Yuan, Chongjian; Liu, Xiyuan; Hong, Xiaoping; Zhang, Fu

doi:10.1109/lra.2021.3098923

Cited by 193 publications

(77 citation statements)

References 17 publications

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“…As demonstrated in (figure 12) below, the colorized point cloud from LiDAR and camera using the ACSC calibration method displays an noticeable error. In comparison, (Yuan et al 2021) calibration method produced a better colorization result than the (Cui et al, 2020) method. The reflectance intensity and colorized point clouds with (Yuan et al 2021) calibration method is presented in (figure 13).…”

Section: Point Cloud Colorization Resultsmentioning

confidence: 87%

“…However, it requires a calibration marker (figure 8) based on the checkerboard pattern and machine learning software package dependencies to work. Automatic calibration approach provided by (Yuan et al 2021) produces the optimal result with a straightforward procedure and without the need for a target marker. Extrinsic parameters of both sensors are obtained from ROS implementation of (Yuan et al 2021) calibration method.…”

Section: Figure 6 Camera Calibration Interfacementioning

confidence: 99%

“…Automatic calibration approach provided by (Yuan et al 2021) produces the optimal result with a straightforward procedure and without the need for a target marker. Extrinsic parameters of both sensors are obtained from ROS implementation of (Yuan et al 2021) calibration method.…”

Section: Figure 6 Camera Calibration Interfacementioning

confidence: 99%

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Open Source and Affordable Terrestrial Laser Scanner

Pyae

Lin

Zaw

2022

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. This paper explores the development of an affordable terrestrial laser scanner (TLS) system based on low-cost components and open source software. This paper enumerates components implemented and integrated in both hardware and software aspects. Primarily, the proposed system depends on Mid-40 LiDAR sensor and utilizes Point Cloud Library (PCL), Open Source Computer Vision Library (OpenCV) and Robotic Operating System (ROS) for system operation and data processing. Furthermore, this paper discusses sensor calibration and fusion methods available and implemented in the processing pipeline. The goal of this work is to produce an open source package of software system and hardware designs of a robust version of the TLS system that can be shared and easily reproduced by individuals and communities for their applications.

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Section: Point Cloud Colorization Resultsmentioning

confidence: 87%

Section: Figure 6 Camera Calibration Interfacementioning

confidence: 99%

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Open Source and Affordable Terrestrial Laser Scanner

Pyae

Lin

Zaw

2022

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…. (m, n) are used to calculate in (17), so the real image coordinates (u 1 , v 1 ), (u 2 , v 2 ) . .…”

Section: Image Distortion Correctionmentioning

confidence: 99%

“…These constraints are composed of Kruppa equations and are used to obtain the intrinsic parameters of the camera [15,16]. Faced with the difficulty of obtaining nonlinear equations, scholars have proposed various methods for self-calibration of cameras [17][18][19]. The biggest advantage of the camera self-calibration technique is its excellent flexibility.…”

Section: Introductionmentioning

confidence: 99%

A New Camera Calibration Technique for Serious Distortion

Huang

Zou

2022

Processes

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A new camera calibration technique based on serious distortion is proposed, which only requires the camera to observe the plane pattern in an arbitrary azimuth. It uses the geometrical imaging principle and radial distortion model to acquire radial lens distortion coefficient and the image coordinate (u0, v0), and then solves the linear equation aiming at the other parameters of the camera. This method has the following characteristics: Firstly, the position of the camera and the plane is arbitrary, and the technique needs only a single observation for plane pattern. Secondly, it is suitable for camera calibration with serious distortion. Thirdly, it does not need expensive ancillary equipment, accurate movement, or lots of photos observed from different orientations. Having been authenticated by computer emulation and actual experiment, the results of the proposed technique have proved to be satisfactory. The research has also paved a new way in camera calibration for further studies.

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