Anzeige
Erschienen in:
2013 | OriginalPaper | Buchkapitel
Representing Motion Patterns with the Qualitative Rectilinear Projection Calculus
verfasst von : Francisco Jose Glez-Cabrera, Jose Vicente Álvarez-Bravo, Fernando Díaz
Erschienen in: Distributed Computing and Artificial Intelligence
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by (Link öffnet in neuem Fenster)
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.
