Abstract
Dealing with surveillance systems, large amount of distance measures are presented in order to classify both normal and abnormal behavior. Typically, techniques based in point-to-point distances are used. However, these techniques do not take into account information about the environment, like pits or restricted areas, for instance. Using a minimal path algorithm to model the usual paths, we develop new trajectory distance measures that are able to introduce information about the scene. The results obtained show promising results.
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BARD, behavioral analysis and recognition dataset, http://www.varpa.org/bard/
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Cancela, B., Ortega, M., Fernández, A., Penedo, M.G. (2013). Trajectory Similarity Measures Using Minimal Paths. In: Petrosino, A. (eds) Image Analysis and Processing – ICIAP 2013. ICIAP 2013. Lecture Notes in Computer Science, vol 8156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41181-6_41
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DOI: https://doi.org/10.1007/978-3-642-41181-6_41
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