Abstract
Reliability and accuracy are key in state of the art Driving Assistance Systems and Autonomous Driving applications. These applications make use of sensor fusion for trustable obstacle detection and classification in any meteorological and illumination condition. Laser scanner and camera are widely used as sensors to fuse because of its complementary capabilities. This paper presents some novel techniques for automatic and unattended data alignment between sensors, and Artificial Intelligence techniques are used to use laser point clouds not only for obstacle detection but also for classification.. Information fusion with classification information from both laser scanner and camera improves overall system reliability.
References
Debattisti, S., Mazzei, L., Panciroli, M.: Automated extrinsic laser and camera inter-calibration using triangular targets. In: 2013 Intelligent Vehicles Symposium (IV), pp. 696−701. IEEE (2013)
Cortes, C., Vapnik, V.: Support vector network. Mach. Learn. 20, 1–25 (1995)
Fremont, V., Bonnifait, P.: Extrinsic calibration between a multi-layer lidar and a camera. In: 2008 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (2008)
García, F., Jiménez, F., Naranjo, J.E., Zato, J.G., Aparicio, F., Armingol, J.M., de la Escalera, A.: Environment perception based on LIDAR sensors for real road applications. Robotica 30, 185–193 (2012)
García, F., García, J., Ponz, A., de la Escalera, A., Armingol, J.M.: Context aided pedestrian detection for danger estimation based on laser scanner and computer vision. Expert Syst. Appl. 41(15), 6646–6661 (2014)
Kwak, K., Huber, D.F., Badino, H., Kanade, T.: Extrinsic calibration of a single line scanning lidar and a camera. In: IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 3283−3289 (2011)
Li, Y., Ruichek, Y., Cappelle, D.: 3D triangulation based extrinsic calibration between a stereo vision system and a LIDAR. In: 14th International IEEE Conference on Intelligent Transpprtation Systems, pp. 797−802 (2011)
Li, Y., Liu, Y., Dong, L., Cai, X.: An algorithm for extrinsic parameters calibration of a camera and a laser range finder using line features. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (2007)
Lisca, G., Jeong, P.J.P., Nedevschi, S.: Automatic one step extrinsic calibration of a multi layer laser scanner relative to a stereo camera. In: 2010 IEEE International Conference on Intelligent Computer Communication and Processing (ICCP) (2010)
Martín, D., García, F., Musleh, B., Olmeda, D., Marín, P., Ponz, A., Rodríguez, C.H., Al-Kaff, A., de la Escalera, A., Armingol, J.M.: IVVI 2.0: an intelligent vehicle based on computational perception. Expert Syst. Appl. 41, 7927–7944 (2014)
Premebida, C., Ludwig, O., Nunes, U.: LIDAR and vision-based pedestrian detection system. J. Field Robot. 26, 696–711 (2009)
Premebida, C., Ludwig, O., Silva, M., Nunes, U.: A cascade classifier applied in pedestrian detection using laser and image-based features. In: Transportation, pp. 1153−1159 (2010)
Rodríguez-Garavito, C.H., Ponz, A., García, F., Martín, D., de la Escalera, A., Armingol, J.M.: Automatic laser and camera extrinsic calibration for data fusion using road plane (2014)
Sick, LD-MRS Manual. SICK AG Waldkirch, Reute, Germany (2009)
Spinello, L., Siegwart, R.: Human detection using multimodal and multidimensional features. In: IEEE International Conference on Robotics and Automation, pp. 3264−3269 (2008). doi:10.1109/ROBOT.2009.4543708
WHO, Global status report on road safety. Time for action. WHO library cataloguing-in-publication data, World Health Organization, Geneva, Switzerland (2009). ISBN 978-9-241563-84-0
Zezhi, C., Pears, N., Freeman, M., Austin, J.: Road vehicle classification using support vector machines. 2009 IEEE Int. Conf. Intell. Comput. Intell. Syst. ICIS 2009 4, 214–218 (2009). doi:10.1109/ICICISYS.2009.5357707
Acknowledgements
This Work Was Supported by the Spanish Government through the CICYT Project (TRA2013-48314-C3-1-R).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Ponz, A., Rodríguez-Garavito, C.H., García, F., Lenz, P., Stiller, C., Armingol, J.M. (2015). Laser Scanner and Camera Fusion for Automatic Obstacle Classification in ADAS Application. In: Helfert, M., Krempels, KH., Klein, C., Donellan, B., Guiskhin, O. (eds) Smart Cities, Green Technologies, and Intelligent Transport Systems. SMARTGREENS VEHITS 2015 2015. Communications in Computer and Information Science, vol 579. Springer, Cham. https://doi.org/10.1007/978-3-319-27753-0_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-27753-0_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-27752-3
Online ISBN: 978-3-319-27753-0
eBook Packages: Computer ScienceComputer Science (R0)