The formulation of models based on abstraction levels has led to the implementation of non-cohesive systems neverless which are not able to fluently communicate among themselves. For this reason, it is necessary to provide new common and transverse knowledge layers among these levels including new semantic relationships. The goal of this strategy is the close interaction among semantically similar layers to the automatic generation of new knowledge. Inhibitors,Modulators,Libraries With the advent of new sensors, we advocate for the addition of a representation layer based on mereology and meronymy. Meronymy studies part-whole relations from a linguistics and cognitive science perspective. Mereology is a close concept, which concerns the formal ontological investigation of the part-whole relation and it is formally expressed in terms of first-order logic.
The idea of employing a part-based layer to support the statements of the scene object abstraction level in a cognitive architecture has been previously suggested by Pinz et al. [12]. Our proposal goes further and seeks to provide a symbolic layer based on the formal definition, development Inhibitors,Modulators,Libraries patterns and implementation of part-whole relationships.Symbolic data representations allow to develop cognitive models able to represent more accurately the complexity of the scene. These models can analyze systematically the knowledge of the scene to discover and describe data related with activities developed by a subject fusing its representation with high-level context knowledge��the set of circumstances surrounding a situation of interest that are potentially of relevance to its completion [13].
A key part of such analysis is currently supported by the approaches emerged from a cognitive view of the traditional computer vision techniques. The ties between meronymy and the current qualitative approaches [14,15] in cognitive vision��mainly Inhibitors,Modulators,Libraries focused on a Inhibitors,Modulators,Libraries qualitative description of spatio-temporal aspects [16]��must be regarded as crucial to narrow the gap of knowledge in activity recognition approaches.This paper describes an ontology-based model for data acquired from recognition algorithms through light wave technology. This model is incorporated into a cognitivist [17] (According to Vernon’s definition ��Cognitivism asserts that cognition involves computations defined Anacetrapib over symbolic representations, in a process whereby information about the world is abstracted by perception, represented using some appropriate symbol set, reasoned about, and then used to plan and act in the world.
��) framework for contextual fusion of 2D visual information previously proposed by our research group [18�C20]. The cornerstone of the framework is an ontological model designed according to the Joint Directors of Laboratories (JDL) fusion model [21] that represents sensor and context information stepped in several levels Brefeldin A protein transport from low-level tracking data to high-level situation knowledge.