Abstract
Tracking targets using multiple cameras is an important processing step for applications such as sports analysis, traffic monitoring, behavior detection and event recognition. The multi-camera tracking problem has been mostly addressed in the literature as detection-based tracking: objects of interest (targets) are first detected and then associated over time [1]. Data from different cameras can be combined either after tracking (in track − first approaches) or before tracking (in fuse − first approaches).
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Yilmaz, A., Javed, O., Shah, M.: Object tracking: A survey. ACM Computing Surveys 38(4), 1–45 (2006)
Anjum, N., Cavallaro, A.: Trajectory association and fusion across partially overlapping cameras. In: Proc. of IEEE Int. Conf. on Advanced Video and Signal Based Surveillance, Genova, IT (September 2009)
Du, W., Piater, J.H.: Multi-Camera People Tracking by Collaborative Particle Filters and Principal Axis-Based Integration. In: Yagi, Y., Kang, S.B., Kweon, I.S., Zha, H. (eds.) ACCV 2007, Part I. LNCS, vol. 4843, pp. 365–374. Springer, Heidelberg (2007)
Stauffer, C., Tieu, K.: Automated multi-camera planar tracking correspondence modeling. In: Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition, Madison, WI, USA (July 2003)
Kang, J., Cohen, I., Medioni, G.: Continuous tracking within and across camera streams. In: Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition, Madison, WI, USA (June 2003)
Morariu, V.I., Camps, O.I.: Modeling correspondences for multi-camera tracking using nonlinear manifold learning and target dynamics. In: Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition, NY, USA (June 2006)
Pham, N.T., Huang, W.: Tracking multiple speakers using CPHD filter. In: Proc. of ACM Int. Conf. on Multimedia, Bavaria, DE (September 2007)
Black, J., Ellis, T., Rosin, P.: Multi view image surveillance and tracking. In: IEEE Int. Workshop on Motion and Video Computing, Orlando, FL, USA (December 2002)
Qu, W., Schonfeld, D., Mohamed, M.: Distributed Bayesian multiple-target tracking in crowded environments using multiple collaborative cameras. EURASIP Journal on Applied Signal Processing (1) (March 2007)
Cai, Q., Aggarwal, J.K.: Tracking human motion in structured environments using a distributed-camera system. IEEE Trans. on Pattern Analysis and Machine Intelligence 21(11), 1241–1247 (1999)
Khan, S., Shah, M.: Consistent labeling of tracked objects in multiple cameras with overlapping fields of view. IEEE Trans. on Pattern Analysis and Machine Intelligence 25(10), 1355–1360 (2003)
Quaritsch, M., Kreuzthaler, M., Rinner, B., Bischof, H., Strobl, B.: Autonomous multicamera tracking on embedded smart cameras. EURASIP Journal on Embedded Systems (October 2007)
Khan, S.M., Shah, M.: Tracking multiple occluding people by localizing on multiple scene planes. IEEE Trans. on Pattern Analysis and Machine Intelligence 31(3), 505–519 (2009)
Fleuret, F., Berclaz, J., Lengagne, R., Fua, P.: Multicamera people tracking with a probabilistic occupancy map. IEEE Trans. on Pattern Analysis and Machine Intelligence 30(2), 267–282 (2008)
Eshel, R., Moses, Y.: Homography based multiple camera detection and tracking of people in a dense crowd. In: Proc. of IEEE Int. Conf. on Computer Vision and Pattern Recognition, Anchorage, AK, USA (June 2008)
Kim, K., Davis, L.S.: Multi-Camera Tracking and Segmentation of Occluded People on Ground Plane Using Search-Guided Particle Filtering. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3953, pp. 98–109. Springer, Heidelberg (2006)
Delannay, D., Danhier, N., De Vleeschouwer, C.: Detection and recognition of sports (wo)man from multiple views. In: Proc. of ACM/IEEE Int. Conf. on Distributed Smart Cameras, Como, IT (August 2009)
Czyz, J., Ristic, B., Macq, B.: A particle filter for joint detection and tracking of color objects. Elsevier Journal of Image and Vision Computing 25, 1271–1281 (2007)
Hadzagic, M., Michalska, H., Lefebvre, E.: Track-before detect methods in tracking low-observable targets: A survey. On-line Magzine: Sensors and Transducers, Special Issue on Multisensor Data and Information Processing 7(2) (August 2005)
Taj, M., Cavallaro, A.: Multi-camera track-before-detect. In: Proc. of ACM/IEEE Int. Conf. on Distributed Smart Cameras, Como, IT (August 2009)
Ristic, B., Arulampalam, S., Gordon, N.: Beyond the Kalman Filter: Particle Filters for Tracking Applications. Artech House, London (2004)
Bruno, M.G.S., Moura, J.M.F.: Multiframe detector/tracker: optimal performance. IEEE Trans. on Aerospace and Electronic Systems 37(3), 925–945 (2001)
Arulampalam, M.S., Maskell, S., Gordon, N., Clapp, T.: A tutorial on particle filters for online nonlinear/non-gaussian Bayesian tracking. IEEE Trans. on Signal Processing 50(2), 174–188 (2002)
Salmond, D.J., Birch, H.: A particle filter for track-before-detect. In: Proc. of the American Control Conference, Arlington, VA, USA (June 2001)
Boers, Y., Driessen, J.N.: Multitarget particle filter track before detect application. IEE Proc.-Radar Sonar Navig. 151(6), 1271–1281 (2004)
Fallon, M., Godsill, S.J.: Multi target acoustic source tracking using track before detect. In: IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, New Paltz, NY, USA (October 2007)
Taj, M., Cavallaro, A.: Multi-view multi-object detection and tracking. In: Computer Vision: Detection, Recognition and Reconstruction, ch. 8, pp. 263–280. Springer Verlag GmbH (2010)
Taj, M., Cavallaro, A.: Distributed and decentralized multi-camera tracking: a survey. IEEE Signal Processing Magazine 28, 46–58 (2011)
Zisserman, A., Hartley, R.I.: Multiple View Geometry in Computer Vision. Cambridge University Press, U.K (2004)
Khan, S.M., Shah, M.: A Multiview Approach to Tracking People in Crowded Scenes Using a Planar Homography Constraint. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3954, pp. 133–146. Springer, Heidelberg (2006)
Doucet, A., Godsill, S., Andrieu, C.: On sequential monte carlo sampling methods for Bayesian filtering. Statistics and Computing 10(3), 197–208 (2000)
Jia, Z., Balasuriya, A., Challa, S.: Vision based data fusion for autonomous vehicles target tracking using interacting multiple dynamic models. Elsevier Journal of Computer Vision and Image Understanding 109(1), 1–21 (2008)
Vermaak, J., Doucet, A., Perez, P.: Maintaining multimodality through mixture tracking. In: Proc. of IEEE Int. Conf. on Computer Vision, Nice, FR, vol. 2 (October 2003)
Comaniciu, D., Meer, P.: Distribution free decomposition of multivariate data. IEEE Trans. on Pattern Analysis and Machine Intelligence 2(1), 22–30 (1999)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer Berlin Heidelberg
About this chapter
Cite this chapter
Taj, M., Cavallaro, A. (2013). Simultaneous Detection and Tracking with Multiple Cameras. In: Cipolla, R., Battiato, S., Farinella, G. (eds) Machine Learning for Computer Vision. Studies in Computational Intelligence, vol 411. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28661-2_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-28661-2_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-28660-5
Online ISBN: 978-3-642-28661-2
eBook Packages: EngineeringEngineering (R0)