Abstract
The Qualitative Rectilinear Projection Calculus (QRPC) is a novel representation model for describing qualitatively motion patterns of two objects through the possible relationships among the rectilinear projection of their trajectories. The paper introduces the key issues of the model (i) the set of geometric relations defined in terms of the front-back and left-right dichotomies, (ii) how it can be possible enumerate an exhaustive set of qualitative states by the composition of these relations and (iii) the possible transitions among states based on the notion of conceptual neighborhood. The representational ability of the model is illustrated by an example extracted from the traffic engineering field where the relative motion of two objects is analyzed and described in terms of the QRPC-states.
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Glez-Cabrera, F.J., Álvarez-Bravo, J.V., Díaz, F. (2013). Representing Motion Patterns with the Qualitative Rectilinear Projection Calculus. In: Omatu, S., Neves, J., Rodriguez, J., Paz Santana, J., Gonzalez, S. (eds) Distributed Computing and Artificial Intelligence. Advances in Intelligent Systems and Computing, vol 217. Springer, Cham. https://doi.org/10.1007/978-3-319-00551-5_31
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DOI: https://doi.org/10.1007/978-3-319-00551-5_31
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-00550-8
Online ISBN: 978-3-319-00551-5
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