nach oben

Machine Vision and Applications

Erschienen in:

02.03.2017 | Original Paper

A distributed approach for real-time multi-camera multiple object tracking

verfasst von: Fabio Previtali, Domenico D. Bloisi, Luca Iocchi

Erschienen in: Machine Vision and Applications | Ausgabe 3-4/2017

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Estimating the positions of a set of moving objects captured from a network of cameras is still an open problem in Computer Vision. In this paper, a distributed and real-time approach for tracking multiple objects on multiple cameras is presented. A quantitative comparison with six state-of-the-art methods has been carried out on the publicly available PETS 2009 data set, demonstrating the effectiveness of the algorithm. Moreover, the proposed method has been tested also on a multi-camera soccer data set, showing its data fusion capabilities.

Vorheriger Artikel Removal of specular reflections from image sequences using feature correspondences

Nächster Artikel Local motion deblurring using an effective image prior based on both the first- and second-order gradients

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Nur mit Berechtigung zugänglich

http://www.dis.uniroma1.it/~previtali.

http://www.cvg.reading.ac.uk/PETS2009.

http://www.milanton.de/data/.

http://www.ino.it/home/spagnolo/Dataset.html.

http://cs-people.bu.edu/jmzhang/tracker_hierarchy/Tracker_Hierarchy.htm.

Dragon, R., Fenzi, M., Siberski, W., Rosenhahn, B., Ostermann, J.: Towards feature-based situation assessment for airport apron video surveillance. In: Outdoor and Large-Scale Real-World Scene Analysis, pp. 110–130. Springer, Berlin, Heidelberg (2012)

Welsh, B.C., Farrington, D.P., Taheri, S.A.: Effectiveness and social costs of public area surveillance for crime prevention. Ann. Rev. Law Soc. Sci. 11(1), 111–130 (2015)CrossRef

Yilmaz, A., Javed, O., Shah, M.: Object tracking: a survey. ACM Comput. Surv. 38(4), 13 (2006)CrossRef

Hu, W., Tan, T., Wang, L., Maybank, S.: A survey on visual surveillance of object motion and behaviors. Trans. Syst. Man Cybern. Part C Appl. Rev. 34(3), 334–352 (2004)CrossRef

Rosencrantz, M., Gordon, G., Thrun, S.: Decentralized sensor fusion with distributed particle filters. In: Conference on Uncertainty in Artificial Intelligence, pp. 493–500 (2002)

Sheng, X., Hu, Y., Ramanathan, P.: Distributed particle filter with GMM approximation for multiple targets localization and tracking in wireless sensor network. In: International Symposium on Information Processing in Sensor Networks, p. 24 (2005)

Ellis, A., Shahrokni, A., Ferryman, J. M.: PETS2009 and winter-pets 2009 results: a combined evaluation. In: International Workshop on Performance Evaluation of Tracking and Surveillance, pp. 1–8 (2009)

D’Orazio, T., Leo, M., Mosca, N., Spagnolo, P., Mazzeo, P.L.: A semi-automatic system for ground truth generation of soccer video sequences. In: International Conference on Advanced Video and Signal Based Surveillance, pp. 559–564 (2009)

Andriyenko, A., Roth, S., Schindler, K.: An analytical formulation of global occlusion reasoning for multi target tracking. In: International Conference on Computer Vision Workshops, pp. 1839–1846 (2011)

10.

Ess, A., Leibe, B., Schindler, K., Van Gool, L.: Robust multiperson tracking from a mobile platform. Trans. Pattern Anal. Mach. Intell. 31(10), 1831–1846 (2009)CrossRef

11.

Zhang, L., Li, Y., Nevatia, R.: Global data association for multi-object tracking using network flows. In: Conference on Computer Vision and Pattern Recognition, pp. 1–8 (2008)

12.

Berclaz, J., Fleuret, F., Turetken, E., Fua, P.: Multiple object tracking using k-shortest paths optimization. Trans. Pattern Anal. Mach. Intell. 33(9), 1806–1819 (2011)CrossRef

13.

Leal-Taixé, L., Pons-Moll, G., Rosenhahn, B.: Everybody needs somebody: modeling social and grouping behavior on a linear programming multiple people tracker. In: International Conference on Computer Vision Workshops, pp. 120–127 (2011)

14.

Henriques, J.F., Caseiro, R., Batista, J.: Globally optimal solution to multi-object tracking with merged measurements. In: International Conference on Computer Vision, pp. 2470–2477 (2011)

15.

Makarenko, A., Durrant-Whyte, H.: Decentralized data fusion and control in active sensor networks. International Conference on Information Fusion, vol. 1, 479–486 (2004)

16.

Black, J., Ellis, T., Rosin, P.: Multi view image surveillance and tracking. In: International Workshop on Motion and Video Computing, pp. 169–174 (2002)

17.

Breitenstein, M.D., Reichlin, F., Leibe, B., Koller-Meier, E., Van Gool, L.: Online multiperson tracking-by-detection from a single, uncalibrated camera. Trans. Pattern Anal. Mach. Intell. 33(9), 1820–1833 (2011)CrossRef

18.

Yang, J., Shi, Z., Vela, P., Teizer, J.: Probabilistic multiple people tracking through complex situations. In: International Workshop on Performance Evaluation of Tracking and Surveillance, pp. 79–86 (2009)

19.

Bae, S., Yoon, K.: Robust online multi-object tracking based on tracklet confidence and online discriminative appearance learning. In: Conference on Computer Vision and Pattern Recognition, pp. 1218–1225 (2014)

20.

Gu, D.: Distributed particle filter for target tracking. In: International Conference on Robotics and Automation, pp. 3856–3861 (2007)

21.

Ong, L., Bailey, T., Durrant-Whyte, H., Upcroft, B.: Decentralised particle filtering for multiple target tracking in wireless sensor networks. In: International Conference on Information Fusion, pp. 1–8 (2008)

22.

Wu, Y., Tong, X., Zhang, Y., Lu, H.: Boosted interactively distributed particle filter for automatic multi-object tracking. In: International Conference on Image Processing, pp. 1844–1847 (2008)

23.

Oreshkin, B.N., Coates, M.J.: Asynchronous distributed particle filter via decentralized evaluation of Gaussian products. In: International Conference on Information Fusion, pp. 1–8 (2010)

24.

Bloisi, D.D., Pennisi, A., Iocchi, L.: Background modeling in the maritime domain. Mach. Vis. Appl. 25(5), 1257–1269 (2014)CrossRef

25.

Bloisi, D.D., Pennisi, A., Iocchi, L.: Parallel multi-modal background modeling. Pattern Recognit. Lett. (2016). doi:10.1016/j.patrec.2016.10.016

26.

Dollar, P., Belongie, S., Perona, P.: The fastest pedestrian detector in the west. In: British Machine Vision Conference, pp. 68.1–68.11 (2010)

27.

Del Moral, P.: Non-linear filtering: interacting particle resolution. Markov Process. Relat. Fields 2(4), 555–581 (1996)MATH

28.

Rokach, L., Maimon, O.: Clustering methods. In: Maimon, O., Rokach, L. (eds) Data Mining and Knowledge Discovery Handbook, pp. 321–352. Springer, New York (2005)

29.

Theodoridis, S., Koutroumbas, K.: Pattern Recognition. Academic Press, London (2003)CrossRefMATH

30.

Heyer, L.J., Kruglyak, S., Yooseph, S.: Exploring expression data: identification and analysis of coexpressed genes. Genome Res. 9(11), 1106–1115 (1999)CrossRef

31.

Kasturi, R., Goldgof, D., Soundararajan, P., Manohar, V., Garofolo, J., Bowers, R., Boonstra, M., Korzhova, V., Zhang, J.: Framework for performance evaluation of face, text, and vehicle detection and tracking in video: data, metrics, and protocol. Trans. Pattern Anal. Mach. Intell. 31(2), 319–336 (2009)CrossRef

32.

Zhang, J., Presti, L.L., Sclaroff, S.: Online multi-person tracking by tracker hierarchy, In: International Conference on Advanced Video and Signal Based Surveillance, pp. 379–385 (2012)

Titel: A distributed approach for real-time multi-camera multiple object tracking
verfasst von: Fabio Previtali
Domenico D. Bloisi
Luca Iocchi
Publikationsdatum: 02.03.2017
Verlag: Springer Berlin Heidelberg
Erschienen in: Machine Vision and Applications / Ausgabe 3-4/2017
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI: https://doi.org/10.1007/s00138-017-0827-5

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 3-4/2017

Superpixel-based class-semantic texton occurrences for natural roadside vegetation segmentation

Movement correction in DCE-MRI through windowed and reconstruction dynamic mode decomposition

Evaluating contour segment descriptors

Motion priors based on goals hierarchies in pedestrian tracking applications

Local motion deblurring using an effective image prior based on both the first- and second-order gradients

Generating natural language tags for video information management