Automatic LiDAR-camera calibration: Extrinsic calibration for a LiDAR-camera pair using structure from motion and stochastic optimization
Typ
Examensarbete för masterexamen
Program
Systems, control and mechatronics (MPSYS), MSc
Publicerad
2022
Författare
Dahlberg, Therese
Strömberg, Valter
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
This thesis presents an approach to automatically and simultaneously perform extrinsic calibration of a LiDAR and a camera. Nowadays, a multitude of sensors are
used in a majority of vehicles. Having correctly calibrated sensors is essential for
attaining accurate data to use in various sensor dependent applications. Today’s
LiDAR-camera calibration methods are often performed manually or require externally introduced calibration objects. However, the method proposed in this thesis
is only dependent on 3D LiDAR point clouds and camera images. The method
consists of two major parts. Firstly, the camera images were converted to 3D point
clouds using a structure from motion pipeline, ensuring that the data from both
sensors were comparable. Secondly, a genetic algorithm with an objective function
based upon a 3D voxel grid filter was used to iteratively compare the overlap of the
point clouds until convergence. The method proved to be successful in creating 3D
point clouds from camera images and accurately estimating the rotational parameters for both sensors. However, it was not as robust and accurate as anticipated
when estimating the sensor positions.
Beskrivning
Ämne/nyckelord
LiDAR-camera calibration , stochastic optimization , genetic algorithm , structure from motion , point clouds