Title :
Automatic calibration of multi-modal sensor systems using a gradient orientation measure
Author :
Taylor, Zeike ; Nieto, John ; Johnson, D.
Author_Institution :
Univ. of Sydney, Sydney, NSW, Australia
Abstract :
A novel technique for calibrating a multi-modal sensor system has been developed. Our calibration method is based on the comparative alignment of output gradients from two candidate sensors. The algorithm is applied to the calibration of the extrinsic parameters of several camera-lidar systems. In this calibration the lidar scan is projected onto the camera´s image using a camera model. Particle swarm optimization is used to find the optimal parameters for this model. This method requires no markers to be placed in the scene. While the system can use a set of scans, unlike many existing techniques it can also automatically calibrate the system reliably using a single scan. The method presented is successfully validated on a variety of cameras, lidars and locations. It is also compared to three existing techniques and shown to give comparable or superior results on the datasets tested.
Keywords :
calibration; cameras; optical radar; particle swarm optimisation; automatic calibration; camera-lidar systems; comparative alignment; gradient orientation measure; multimodal sensor system; optimal parameter; particle swarm optimization; Calibration; Cameras; Equations; Laser radar; Mathematical model; Optimization; Sensors;
Conference_Titel :
Intelligent Robots and Systems (IROS), 2013 IEEE/RSJ International Conference on
Conference_Location :
Tokyo
DOI :
10.1109/IROS.2013.6696516