Ontology construction for annotation of daily activities to video data

Abstract

Observing and analyzing human behavior is a crucial task in the domains of user-centered manufacturing. Video data is an important resource that captures the multimodal features of human behaviors. However, the analysis by manual is still a labor-intensive task such as extraction of interest scene. This paper proposes an ontology to represent human behavior in the video data as a knowledge graph to index the scene of interest.