Abstract
This paper addresses the problem of modeling and automated recognition of video events. We propose to use Linear Temporal Logic as a language for events specification and Fuzzy Semantic Petri Nets (FSPN) as a tool for their recognition. FSPN are Petri nets coupled with an underlying fuzzy ontology. The ontology stores assertions (facts) concerning classification of objects and detected relations. Fuzzy predicates querying the ontology content are used as guards of transitions in FSPN. Tokens carry information on objects participating in a scenario and are equipped with weights indicating likelihood of their assignment to places. In turn, the places correspond to scenario steps. We describe a prototype detection system consisting of an FSPN interpreter, the fuzzy ontology, and a set of predicate evaluators. Initial tests yielding promising results are reported.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
References
Aggarwal, J., Park, S.: Human motion: modeling and recognition of actions and interactions. In: Proceedings of the 2nd International Symposium on 3D Data Processing, Visualization and Transmission, 2004. 3DPVT 2004, pp. 640–647 Sept 2004
Aggarwal, J., Ryoo, M.S.: Human activity analysis: a review. ACM Comput. Surv. (CSUR) 43(3), 16 (2011)
Akdemir, U., Turaga, P., Chellappa, R.: An ontology based approach for activity recognition from video. In: Proceedings of the 16th ACM international conference on Multimedia, pp. 709–712. ACM (2008)
Albanese, M., Chellappa, R., Moscato, V., Picariello, A., Subrahmanian, V.S., Turaga, P., Udrea, O.: A constrained probabilistic Petri net framework for human activity detection in video. IEEE Trans. Multimedia 10(8), 1429–1443 (2008)
Barnard, M., Odobez, J.M., Bengio, S.: Multi-modal audio-visual event recognition for football analysis. In: IEEE 13th Workshop on Neural Networks for Signal Processing, 2003. NNSP’03. 2003, pp. 469–478, Sept 2003
Borzin, A., Rivlin, E., Rudzsky, M.: Surveillance event interpretation using generalized stochastic Petri nets. In: Eighth International Workshop on Image Analysis for Multimedia Interactive Services, 2007. WIAMIS’07, pp. 4–4. IEEE (2007)
Brémond, F., Thonnat, M., Zúniga, M.: Video-understanding framework for automatic behavior recognition. Behav. Res. Methods 38(3), 416–426 (2006)
Büchi, J.R.: On a decision method in restricted second-order arithmetic. In: International Congress on Logic, Methodology, and Philosophy of Science, pp. 1–11. Stanford University Press (1962)
Ghanem, N., DeMenthon, D., Doermann, D., Davis, L.: Representation and recognition of events in surveillance video using Petri nets. In: Conference on Computer Vision and Pattern Recognition Workshop, 2004. CVPRW’04, pp. 112–112, June 2004
Joo, S.W., Chellappa, R.: Attribute grammar-based event recognition and anomaly detection. In: Conference on Computer Vision and Pattern Recognition Workshop, 2006. CVPRW’06, pp. 107–107, June 2006
Kripke, S.: Semantical considerations on modal logic. Acta philosophica fennica 16(1963), 83–94 (1963)
Lavee, G., Rivlin, E., Rudzsky, M.: Understanding video events: a survey of methods for automatic interpretation of semantic occurrences in video. IEEE Trans. Syst. Man Cybern. Part C Appl. Rev. 39(5), 489–504 (2009)
Lavee, G., Rudzsky, M., Rivlin, E., Borzin, A.: Video event modeling and recognition in generalized stochastic Petri nets. IEEE Trans. Circuits Syst. Video Technol. 20(1), 102–118 (2010)
Lukasiewicz, T., Straccia, U.: Managing uncertainty and vagueness in description logics for the semantic web. Web Semant. Sci. Serv. Agents World Wide Web 6(4), 291–308 (2008)
Manna, Z., Pnueli, A.: Temporal logic. In: The Temporal Logic of Reactive and Concurrent Systems, pp. 179–273. Springer, New York (1992)
Munch, D., Jsselmuiden, J., Arens, M., Stiefelhagen, R.: High-level situation recognition using fuzzy metric temporal logic, case studies in surveillance and smart environments. In: IEEE International Conference on Computer Vision Workshops (ICCV Workshops), pp. 882–889 Nov 2011
Nagel, H.H.: Steps toward a cognitive vision system. AI Mag. 25(2), 31 (2004)
Szwed, P.: Video event recognition with Fuzzy Semantic Petri Nets. In: Gruca, D.A., Czachórski, T., Kozielski, S. (eds.) Man-Machine Interactions 3, Advances inIntelligent Systems and Computing, vol. 242, pp. 431–439. Springer International Publishing (2014)
Szwed, P., Komorkiewicz, M.: Object tracking and video event recognition with Fuzzy Semantic Petri Nets. In: Ganzha, M., Maciaszek, L.A., Paprzycki, M. (eds.) FedCSIS, pp. 167–174 (2013)
Acknowledgments
This work is supported from AGH University of Science and Technology under Grant No. 11.11.120.859.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Szwed, P. (2016). Modeling and Recognition of Video Events with Fuzzy Semantic Petri Nets. In: Skulimowski, A., Kacprzyk, J. (eds) Knowledge, Information and Creativity Support Systems: Recent Trends, Advances and Solutions. Advances in Intelligent Systems and Computing, vol 364. Springer, Cham. https://doi.org/10.1007/978-3-319-19090-7_38
Download citation
DOI: https://doi.org/10.1007/978-3-319-19090-7_38
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-19089-1
Online ISBN: 978-3-319-19090-7
eBook Packages: Computer ScienceComputer Science (R0)