Abstract
Over the last decade, there has been a significant deployment of systems dedicated to surveillance. These systems make use of real-time sensors that generate continuous streams of data. Despite their success in many cases, the increased number of sensors leads to a cognitive overload for the operator in charge of their analysis. However, the context and the application requires an ability to react in real-time. The research presented in this paper introduces a spatio-temporal-based approach the objective of which is to provide a qualitative interpretation of the behavior of an entity (e.g., a human or vehicle). The process is formally supported by a fuzzy logic-based approach, and designed in order to be as generic as possible.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
Allen, J.F., Ferguson, G.: Actions and events in interval temporal logic. Journal of Logic and Computation 4(5), 531–579 (2010)
Shet, V., Harwood, D., Davis, L.: VidMAP: Video monitoring of activity with Prolog. In: IEEE International Conference on Advanced Video and Signal based Surveillance, Como, Italy, pp. 224–229. IEEE Computer Society (2005)
Geerinck, T., Enescu, V., Ravyse, I., Sahli, H.: Rule-based video interpretation framework: Application to automated surveillance. In: Proceedings of the 5th International Conference on Image and Graphics, pp. 341–348. IEEE Computer Society, Washington, DC (2009)
Krausz, B., Herpers, R.: Metrosurv: Detecting events in subway stations. Multimedia Tools and Applications 50(1), 123–147 (2010)
Ghanem, N., Dementhon, D., Doermann, D., Davis, L.: Representation and recognition of events in surveillance video using petri nets. In: Proceedings of the Conference on Computer Vision and Pattern Recognition Workshops. IEEE Computer Society, Washington, DC (2004)
Bremond, F., Medioni, G.: Scenario recognition in airborne video imagery. In: Proceedings of the Conference on Computer Vision and Pattern Recognition Workshops, Santa Barbara, CA, USA. IEEE Computer Society (1998)
Van de Weghe, N., Cohn, A., Maeyer, P., Witlox, F.: Representing moving objects in computer-based expert systems: the overtake event example. Expert Systems with Applications 29, 977–983 (2005)
Noyon, V., Claramunt, C., Devogele, T.: A relative representation of trajectories in geographical spaces. GeoInformatica 11(4), 479–496 (2007)
Gottfried, B.: Interpreting motion events of pairs of moving objects. GeoInformatica 15(2), 247–271 (2011)
Erwig, M.: Toward spatiotemporal patterns. Spatio-Temporal Databases 1, 29–54 (2004)
Hornsby, K.S., King, K.: Modeling motion relations for moving objects on road networks. GeoInformatica 12(4), 477–495 (2008)
Zadeh, L.A.: Fuzzy sets. Information and Control 8(3), 338–353 (1965)
Arens, M., Nagel, H.-H.: Behavioral Knowledge Representation for the Understanding and Creation of Video Sequences. In: Günter, A., Kruse, R., Neumann, B. (eds.) KI 2003. LNCS (LNAI), vol. 2821, pp. 149–163. Springer, Heidelberg (2003)
Lynch, K.: The Image of the City. The MIT Press, Boston (1960)
Smith, B., Varzi, A.: Fiat and Bona Fide Boundaries: Towards an Ontology of Spatially Extended Objects. In: Frank, A.U. (ed.) COSIT 1997. LNCS, vol. 1329, pp. 103–119. Springer, Heidelberg (1997)
Zhan, F.B.: Approximate analysis of binary topological relations between geographic regions with indeterminate boundaries. Soft Computing - A Fusion of Foundations, Methodologies and Applications 2, 28–34 (1998)
Hudelot, C., Atif, J., Bloch, I.: Fuzzy spatial relation ontology for image interpretation. Fuzzy Sets Systems 159(15), 1929–1951 (2008)
Clementini, E., Felice, P.D.: Approximate topological relations. International Journal of Approximate Reasoning 16(2), 173–204 (1997)
Cohn, A.G., Gotts, N.M.: The ‘egg-yolk’ representation of regions with indeterminate boundaries. In: Burrough, P., Frank, A.M. (eds.) Specialist Meeting on Spatial Objects with Undetermined Boundaries, pp. 171–187. Taylor & Francis (1997)
Allen, J.F.: Maintaining knowledge about temporal intervals. Communication of the ACM 26(11), 832–843 (1983)
Schockaert, S., Cock, M.D., Kerre, E.E.: Fuzzifying Allen’s temporal interval relations. IEEE Transactions on Fuzzy Systems 16(2), 517–533 (2008)
Cariǹena, P., Bugarin, A., Mucientes, M., Barro, S.: A language for expressing fuzzy temporal rules. Mathware & Soft Computing 7, 213–227 (2000)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Le Yaouanc, JM., Poli, JP. (2012). A Fuzzy Spatio-temporal-Based Approach for Activity Recognition. In: Castano, S., Vassiliadis, P., Lakshmanan, L.V., Lee, M.L. (eds) Advances in Conceptual Modeling. ER 2012. Lecture Notes in Computer Science, vol 7518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33999-8_37
Download citation
DOI: https://doi.org/10.1007/978-3-642-33999-8_37
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33998-1
Online ISBN: 978-3-642-33999-8
eBook Packages: Computer ScienceComputer Science (R0)