Multi-Camera Structure from Motion with Eye-to-Eye Calibration
Imaging systems consisting of multiple conventional cameras are of increasing interest for computer vision applications such as Structure from Motion (SfM) due to their large combined field of view and high composite image resolution. In this work we present a SfM framework for multi-camera systems w/o overlapping camera views that integrates on-line extrinsic camera calibration, local scene reconstruction, and global optimization based on combining hand-eye calibration methods with standard SfM. For this purpose, we propose a novel method for extrinsic calibration based on rigid motion constraints that uses visual measurements directly instead of motion correspondences. Only a single calibration pattern visible within the view of one camera is needed to provide an accurate reconstruction with absolute scale.
- 1.Andreff, N., Horaud, R., Espiau, B.: On-line hand-eye calibration. In: 2nd International Conference on 3D Digital Imaging and Modeling, pp. 430–436 (1999)Google Scholar
- 2.Bradski, G.: The OpenCV library. Dr. Dobb’s J. Softw. Tools 25(11), 120–126 (2000)Google Scholar
- 4.Chen, H.H.: A screw motion approach to uniqueness analysis of head-eye geometry. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 145–151 (1991)Google Scholar
- 8.Farenzena, M., Fusiello, A., Gherardi, R.: Structure-and-motion pipeline on a hierarchical cluster tree. In: IEEE International Conference on Computer Vision Workshops, pp. 1489–1496 (2009)Google Scholar
- 11.Hesch, J.A., Mourikis, A.I., Roumeliotis, S.I.: Mirror-based extrinsic camera calibration. In: Workshop on the Algorithmic Foundations of Robotics, pp. 285–299 (2008)Google Scholar
- 13.Kumar, R.K., Ilie, A., Frahm, J.M., Pollefeys, M.: Simple calibration of non-overlapping cameras with a mirror. In: IEEE Conference on Computer Vision and Pattern Recognition, pp. 1–7 (2008)Google Scholar
- 14.Lébraly, P., Royer, E., Ait-Aider, O., Deymier, C., Dhome, M.: Fast calibration of embedded non-overlapping cameras. In: IEEE International Conference on Robotics and Automation, pp. 221–227 (2011)Google Scholar
- 15.Li, B., Heng, L., Köser, K., Pollefeys, M.: A multiple-camera system calibration toolbox using a feature descriptor-based calibration pattern. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 1301–1307 (2013)Google Scholar
- 17.Lourakis, M.I.A., Argyros, A.A.: The design and implementation of a generic sparse bundle adjustment software package based on the Levenberg-Marquardt algorithm. Technical report #340, Institute of Computer Science, Foundation for Research and Technology - Hellas (FORTH) (2004)Google Scholar
- 18.Moré, J.J., Garbow, B.S., Hillstrom, K.E.: User guide for MINPACK-1. Technical report ANL-80-74, Argonne National Laboratory (1980)Google Scholar
- 19.Newcombe, R.A., Lovegrove, S., Davison, A.J.: DTAM: Dense tracking and mapping in real-time. In: IEEE International Conference on Computer Vision, pp. 2320–2327 (2011)Google Scholar
- 20.Pagel, F.: Calibration of non-overlapping cameras in vehicles. In: IEEE Intelligent Vehicles Symposium, pp. 1178–1183 (2010)Google Scholar
- 22.Rodríguez, A.L., de Teruel, P.E.L., Ruiz, A.: GEA optimization for live structureless motion estimation. In: IEEE International Conference on Computer Vision, pp. 715–718 (2011)Google Scholar
- 23.Strobl, K.H., Hirzinger, G.: Optimal hand-eye calibration. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 4647–4653 (2006)Google Scholar
- 24.Terzakis, G., Culverhouse, P., Bugmann, G., Sharma, S., Sutton, R.: A recipe on the parameterization of rotation matrices for non-linear optimization using quaternions. Technical report MIDAS.SMSE.2012.TR.004, Marine and Industrial Dynamic Analysis School of Marine Science and Engineering, Plymouth University (2012)Google Scholar
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