Abstract :
[en] In this paper, we present an approach for semantic annotation of movement in the videos that is based on ontology model and semantic concept classifiers. The video movement ontology (VMO) is defined by using OWL (Ontology Web Language), and included both schema and data. In fact, ontology concepts and their relationships that construct the movement model are based on the semantics of the Benesh Movement Notation (BMN), which can describe any form of dance or human movement. We have exploited the knowledge embedded into the ontology by using Semantic Web Rules Language (SWRL). In our approach, SWRL rules are used to perform rule-based reasoning over both concepts and concept instances, and to improve the quality of movement annotation in the video. Additionally, we can search within the VMO by writing SPARQL queries. According to the authors' knowledge, this is the first time the ontology concept is used to annotate with BMN the video human movements.
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