Multi-mode Fusion Semantic Extraction Model Based on Ontology
Mi Li · Computer Technology and Development · 2013
There're two key technologies for semantic based video retrieval has to deal with.One is to bridge the semantic gap between low-level features and high-level semantic concepts.The other is to build a effective semantic model.In this paper,based on the multi-level semantic analysis of video,employ an effective object segmentation method on extracting the semantic object in video,and use semantic object as the middle level and consider the fusion of multi-model,such as image,sound and text,to bridge semantic gap.Meanwhile,videos contain multi-granularity semantic concepts.And since it has superiority to describe concepts and relationships between them,propose a ontology-based semantic model,to reason compound concept of higher level from atomic concepts,which are extracted from image,sound and text.By using this semantic extraction model,can get the video semantics contain richer semantic level and semantic granularity.Thus it can be closer to the semantic concepts in human thoughts.