Abstract
Today, a number of positioning technologies exist in order to track moving objects. While GPS devices enable wayfinding in outdoor environments, several techniques have been devised for indoor tracking, to enable smart spaces, for example. But even at the microscopic scale objects are tracked by researchers of the natural sciences with imaging technologies. Regardless of the spatial scale and application at hand, a common problem consists in the ever growing quantities of movement data which are to be managed. One strategy asks for how to simplify the data, such that compact representations save space but do still capture relevant information. Such an abstraction is described in this paper. It is shown how it can be applied to constraint programming techniques in order to search for movement patterns of groups of objects. Instead of exhaustively searching by means of generate and test, the representation allows the application of constraint propagation. As a consequence, search space can be reduced significantly. Moreover, it is shown how the chosen representation aids the dealing with a specific class of imprecise data. The domain of biological cells is used for illustrating the presented methods. The resulting observations, made by light microscopes, suffer from the addressed class of imprecise data.
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References
Dylla, F.: Qualitative Spatial Reasoning for Navigating Agents. In: Gottfried, B., et al. (eds.) BMI – Smart Environments, pp. 98–128. IOS Press, Amsterdam (2009)
Egenhofer, M., Franzosa, R.: Point-Set Topological Spatial Relations. International Journal of Geographical Information Systems 5(2), 161–174 (1991)
Friedl, P., Zänker, K.S., Bröcker, E.-B.: Cell migration strategies in 3-D extracellular matrix: Differences in morphology, cell matrix interactions, and integrin function. Microscopy Research and Technique 43(5), 369–378 (1998)
Gottfried, B.: Reasoning about Intervals in Two Dimensions. In: Thissen, W., et al. (eds.) IEEE Int. Conf. on Systems, Man & Cybernetics: The Hague, The Netherlands, October 10-13, pp. 5324–5332. IEEE Press, Los Alamitos (2004)
Gottfried, B.: Representing short-term observations of moving objects by a simple visual language. Journal of Visual Languages and Computing 19, 321–342 (2008)
Kurata, Y., Egenhofer, M.: Interpret. of Behav. from a Viewpoint of Topology. In: Gottfried, B., et al. (eds.) BMI – Smart Envir., pp. 75–97. IOS Press, Amsterdam (2009)
Laube, P.: Progress in Movement Pattern Analysis. In: Gottfried, B., Aghajan, H. (eds.) BMI – Smart Environments, pp. 43–71. IOS Press, Amsterdam (2009)
Millonig, A., Brändle, N., Ray, M., Bauer, D., Van Der Spek, S.: Pedestrian Behaviour Monitoring: Methods and Experiences. In: Gottfried, B., et al. (eds.) BMI – Smart Environments, pp. 11–42. IOS Press, Amsterdam (2009)
Moeller, J., Gottfried, B., Schlieder, C., Herzog, O., Friedl, P.: Automated Tracking of Cell Movements and Resolution of Cell-Cell Collisions in Three-dimensional Collagen Matrices. In: Keystone-Symposium on Cell-Analysis, Colorado, USA (2003)
Randell, D.A., Cui, Z., Cohn, A.G.: A spatial logic based on regions and connection. In: 3rd Int. Conf. on Knowledge Representation and Reasoning, San Mateo, pp. 165–176. Morgan Kaufman, San Francisco (1992)
Wood, Z., Galton, A.: Collectives and their Movement Patterns. In: Gottfried, B., Aghajan, H. (eds.) Behaviour Monitoring and Interpretation – Smart Environments, pp. 129–155. IOS Press, Amsterdam (2009)
Zhang, B., Zimmer, C., Olivo-Marin, J.-C.: Tracking fluorescent cells with coupled geometric active contours. In: IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 476–479. IEEE Press, Los Alamitos (2004)
Zimmermann, K., Freksa, C.: Qualitative Spatial Reasoning Using Orientation, Distance and Path Knowledge. Applied Intelligence 6, 49–58 (1996)
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Gottfried, B. (2010). Searching for Locomotion Patterns that Suffer from Imprecise Details. In: Dillmann, R., Beyerer, J., Hanebeck, U.D., Schultz, T. (eds) KI 2010: Advances in Artificial Intelligence. KI 2010. Lecture Notes in Computer Science(), vol 6359. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16111-7_19
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DOI: https://doi.org/10.1007/978-3-642-16111-7_19
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