Abstract
Gait recognition involves the automatic classification of human people from sequences of data about their movement patterns. This paper describes our ongoing work in the development of a gait recognition system using Microsoft Kinect data and based on fuzzy ontologies to manage the imprecision of the data and to improve the system scalability.
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Acknowledgement
We were funded by DGA/FEDER and projects UZCUD 2016-TEC-02 (University of Zaragoza and Defense University Center), TIN2013-46238-C4 and TIN2016-78011-C4 (Ministerio de EconomÃa y Competitividad).
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Bobillo, F., Dranca, L., Bernad, J. (2017). A Fuzzy Ontology-Based System for Gait Recognition Using Kinect Sensor. In: Moral, S., Pivert, O., Sánchez, D., MarÃn, N. (eds) Scalable Uncertainty Management. SUM 2017. Lecture Notes in Computer Science(), vol 10564. Springer, Cham. https://doi.org/10.1007/978-3-319-67582-4_29
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