Abstract
Abstract. We propose using the relative orientation model (ROM) of panoramic to register the MMS LiDAR points and panoramic image sequence, which has the wide applicability. The feature points, extracted and matched from panoramic image pairs, are used to solve the relative position and attitude parameters in the ROM, then, combining the absolute position and attitude parameters of the initial panoramic image, the MMS LiDAR points and panoramic image sequence are registered. First, we propose the position/attitude ROM (PA-ROM) and attitude ROM (A-ROM) of panoramic images respectively, which are apply to the position/attitude parameters both unknown and only the attitude parameters unknown. Second, we automatically extract and match feature points from panoramic image pairs using the SURF algorithm, as these mismatching points will affect the registration accuracy, the RANSAC algorithm and ROM were used to choose the best matching points automatically. Finally, we select the feature points manually from MMS LiDAR points and panoramic image sequence as the checkpoints, and then compare the registration accuracy of continuous/discontinuous panoramic image pairs. The results show that MMS LiDAR points and panoramic image sequence are registered accurately based on ROM (7.36 and 3.75 pixels in dataset I and II), what's more, our registration method just tackle the image pairs (uninvolved LiDAR points), so it is suitable for more road scenes.
Highlights
Mobile mapping systems (MMS) have been extensively used for spatial data acquisition, which can obtain optical image sequence (2D) and LiDAR points (3D) simultaneously
Zhu et al (Zhu et al, 2019) proposed utilizing the feature points of road lamp and lane to register MMS LiDAR points and panoramic image sequence, which are extracted from LiDAR points and images, the mean registration accuracy is 5.84 pixels calculated by 31 panoramic images; this method will failure in the scene without road lamp and lane
We propose the registration method of MMS LiDAR points and panoramic image sequence based on relative orientation model (ROM), which includes the Position/Attitude ROM (PA-ROM) and Attitude ROM (A-ROM) of panoramic image, extract and match feature points, and the registration accuracy evaluation
Summary
Mobile mapping systems (MMS) have been extensively used for spatial data acquisition, which can obtain optical image sequence (2D) and LiDAR points (3D) simultaneously. The Original registration method directly obtains the position and orientation parameters from GPS/IMU, but the accuracy is affected by dropouts, etc., which lead to unreliable registration result (Miled et al, 2016) Another common method is Point-based registration method, it has the accurate precision, but automatically extract and match feature points from LiDAR points and panoramic image sequence is difficult, and the manual selection in image sequence is unrealistic. Zhu et al (Zhu et al, 2019) proposed utilizing the feature points of road lamp and lane to register MMS LiDAR points and panoramic image sequence, which are extracted from LiDAR points and images, the mean registration accuracy is 5.84 pixels calculated by 31 panoramic images; this method will failure in the scene without road lamp and lane. Plane map of the MMS LiDAR points (1600×1600, 320m×320m) and the panoramic image sequence, the red dots and number express 10 panoramic images (No.1-10)
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