Video Semantic Extraction Based on Simfusion and Ontology
LI Guang-cui · Jisuanji gongcheng · 2011
Most of the researches in extracting semantic concepts do not consider the temporal associated co-occurrence characteristic of multimodes,and label the training set using self-define concepts,thus affecting the accuracy of semantic concepts extraction.Aiming at these problems,this paper brings forward a new approach based on Simfusion algorithm and labeling the training set using ontology repository to extract semantic concepts of video.The method extracts key-frame according to the content of the shots,and makes the most of temporal associated co-occurrence characteristic during in multimode.Meanwhile,the method labels the sample set using the ontology repository and training classifier,thus offsetting insufficiency in subjectivity,incorrect.Experimental result shows that the method can get a better accuracy,well operability and universality in the research of semantic concepts of video.