Video Semantic Content Analysis Using Extensions to OWL

Jianyun Chen · Journal of National University of Defense Technology · 2010

Due to the rapid increase in the amount of available video data,there has been a growing demand for efficient methods to understand and manage the data at the semantic level. In this paper,the V-OWL is proposed with extensions to OWL,which can describe complex video content including temporal-spatial and uncertain relationships. The B-Graph description model based on Bayesian Net is proposed to map the concepts and relationships in V-OWL ontology into the nodes and edges in B-Graph. Video semantic content can be discovered automatically by using existing training and reasoning methods of Bayesian Net. Results from experiments show that V-OWL has achieved good description of complex video content,and satisfactory precision and recall of high level semantic content detections.

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