Abstract
In areas with insufficient GPS reception, like in urban areas close to buildings, alternative techniques have to be used to assist the inertial navigation system. The long-term objective of this work is to use buildings, detected in camera images, as distinctive landmarks for navigating micro aerial vehicles within the aforementioned areas. This paper presents a new method to detect buildings in aerial images. To use this algorithm onboard the vehicle during the mission, it has to be fast and executed automatically without readjusting any parameters by the operator. To cover a wide range of possible application areas, no building constraints are required. Therefore a wide variation of buildings with complex shapes can be detected.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Comport, A., Malis, E., and Rives, E., Accurate quadrifocal tracking for robust 3d visual odometry, IEEE International Conference on Robotics and Automation, 2007.
Howard, A., Real-time stereo visual odometry for autonomous ground vehicles, IEEE International Conference on Intelligent Robots and Systems, 2008.
Matthies, L. and Shafer, S., Error modeling in stereo navigation, IEEE Journal of Robotics and Automation, 1987.
Milella, A. and Siegwart, R., Stereo-based ego-motion estimation using pixel tracking and iterative closest point, IEEE International Conference on Computer Vision Systems, 2006.
Lacroix, S. et al., Rover self localization in planetarylike environments, International Symposium on Artificial Intelligence, Robotics, and Automation for Space, 1999.
Nistér, D., Naroditsky., O., and Bergen, J., Visual odometry for ground vehicle applications, Journal of Field Robotics, 2006.
Campbell, J., Sukthankar, R., and Pahwa, A., A robust visual odometry and precipice detection system using consumergrade monocular vision, IEEE International Conference on Robotics and Automation, 2005.
Tardif, J., Pavlidis, K., and Daniilidis, K., Monocular visual odometry in urban environments using an omnidirectional camera, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2008.
Stradsdat, H., Montiel, J.M., and Davison, A.J., Scale drift-aware large scale monocular slam, Proceedings of the Robotics: Science and Systems Conference, 2010.
Davison, A.J. et al., Real-time single camera slam, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2007.
Abdulrahim, K. et al., Aiding MEMS IMU with building heading for indoor pedestrian navigation, Ubiquitous Positioning Indoor Navigation and Location Based Service, 2010.
Kummerle, R. et al., Large scale graph-based SLAM using aerial images as prior information, Proceedings of Robotics: Science and Systems, 2009.
Leung, K. Clark, C., and Huissoon, J., Localization in urban environments by matching ground level video images with an aerial image, ICRA, 2008.
Shorter, N. and Kasparis, T., Automatic vegetation identification and building detection from a single nadir aerial image, Remote Sensing, 2009.
Müller, S. and Zaum, D., Robust building detection in aerial images, International Archives of Photogrammetry and Remote Sensing, 2005.
Cote, M. and Saeedi, P., Automatic rooftop extraction in nadir aerial imagery of suburban regions using corners and variational level set evolution, IEEE Transactions on Geoscience and Remote Sensing, 2013.
Chunming, Li, et al. Distance regularized level set evolution and its application to image segmentation, IEEE Transactions on Image Processing, 2010.
Izadi, M. and Saeedi, P., Automatic building detection in aerial images using a hierarchical feature based image segmentation, Pattern Recognition (ICPR), 2010.
Comaniciu, D. and Meer, P., Mean shift: a robust approach toward feature space analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, 2002.
Frette, O. and Virnovsky, G., Estimation of the curvature of an interface from a digital 2D image, Computational Materials Science 44, 2009.
Author information
Authors and Affiliations
Corresponding author
Additional information
Published in Giroskopiya i Navigatsiya, 2014, No. 4, pp. 99–110.
Rights and permissions
About this article
Cite this article
Popp, M., Granacher, R. & Trommer, G.F. Automatic detection of complex shaped buildings in aerial images to support the navigation of micro aerial vehicles in urban environment. Gyroscopy Navig. 6, 1–8 (2015). https://doi.org/10.1134/S2075108715010095
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1134/S2075108715010095