Abstract
This article presents a novel framework to register and fuse heterogeneous sensory data. Our approach is based on geometrically registration of sensory data onto a set of virtual parallel planes and then applying an occupancy grid for each layer. This framework is useful in surveillance applications in presence of multi-modal sensors and can be used specially in tracking and human behavior understanding areas. The multi-modal sensors set in this work comprises of some cameras, inertial measurement sensors (IMU), laser range finders (LRF) and a binaural sensing system. For registering data from each one of these sensors an individual approach is proposed. After registering multi-modal sensory data on various geometrically parallel planes, a two-dimensional occupancy grid (as a layer) is applied for each plane.
Chapter PDF
References
Smith, D., Singh, S.: Approaches to multisensor data fusion in target tracking: A survey. IEEE Transactions on Knowledge and Data Engineering 18, 1696–1710 (2006)
Armesto, L., Tornero, J.: On multi-rate fusion for non-linear sampled-data systems: Application to a 6d tracking system. Robotics and Autonomous Systems. Elsevier, Amsterdam (2007)
Bellotto, N., Hu, H.: Vision and laser data fusion for tracking people with a mobile robot. In: Proceedings of the 2006 IEEE International Conference on Robotics and Biomimetics, Kunming, China (2006)
Chakravarty, J.: Panoramic vision and laser range finder fusion for multiple person tracking. In: 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS (2006)
Khan, S.M., Yan, P., Shah, M.: A homographic framework for the fusion of multi-view silhouettes. In: IEEE 11th International Conference on Computer Vision, ICCV 2007 (2007)
Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge (2003)
Aliakbarpour, H., Nunez, P., Prado, J., Khoshhal, K., Dias, J.: An efficient algorithm for extrinsic calibration between a 3d laser range finder and a stereo camera for surveillance. In: 14th International Conference on Advanced Robotics, ICAR 2009 (2009)
Ferreira, J.F., Pinho, C., Dias, J.: Implementation and calibration of a Bayesian binaural system for 3d localisation. In: IEEE International Conference on Robotics and Biomimetics (ROBIO 2008), Bangkok, Tailand, December 2008, pp. 14–17 (2008)
Pinho, C., Ferreira, J.F., BessiÚre, P., Dias, J.: A Bayesian binaural system for 3d sound-source localisation. In: International Conference on Cognitive Systems (CogSys 2008), pp. 109–114 (2008)
Mirisola, L.G.B., Dias, J.: Tracking from a moving camera with attitude estimates. In: ICR 2008 (2008)
Mirisola, L.G.B.: Exploiting attitude sensing in vision-based navigation, mapping and tracking including results from an airship. PhD thesis (2009)
Lobo, J., Dias, J.: Relative pose calibration between visual and inertial sensors. International Journal of Robotics Research, Special Issue 2nd Workshop on Integration of Vision and Inertial Sensors 26, 561–575 (2007)
Criminisi, A.: Accurate visual metrology from single and multiple uncalibrated images. PhD thesis, Oxford (1999)
Mekhnacha, K., Mao, Y., Raulo, D., Laugier, C.: Bayesian occupancy filter based fast clustering-tracking algorithm. In: IROS 2008 (2008)
Fleuret, F., Jerome Berclaz, R.L., Fua, P.: Multi-camera people tracking with a probabilistic occupancy map. IEEE Transactions on Pattern Analysis and Machine Intelligence (2008)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 IFIP International Federation for Information Processing
About this paper
Cite this paper
Aliakbarpour, H., Ferreira, J.F., Khoshhal, K., Dias, J. (2010). A Novel Framework for Data Registration and Data Fusion in Presence of Multi-modal Sensors. In: Camarinha-Matos, L.M., Pereira, P., Ribeiro, L. (eds) Emerging Trends in Technological Innovation. DoCEIS 2010. IFIP Advances in Information and Communication Technology, vol 314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11628-5_33
Download citation
DOI: https://doi.org/10.1007/978-3-642-11628-5_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11627-8
Online ISBN: 978-3-642-11628-5
eBook Packages: Computer ScienceComputer Science (R0)