一个知识辅助的视频语义概念探测框架

视频语义概念探测是视频语义内容分析研究领域的热点和难点问题.语义概念探测方法的性能取决于其是否能够有效地建模和匹配视频语义内容特征.将视频内容抽象为感知概念和语义概念以及概念间的关系,提出了知识辅助的视频语义概念探测框架,利用本体建模概念间关系和上下文知识,从低层特征匹配和上下文匹配两个方面综合考虑语义概念的探测.通过线性融和策略,对匹配结果进行融合得到最终的探测结果.实验结果表明提出的方法探测性能良好.

A knowledge-assisted framework for video semantic concept detection

Semantic concept detection in video is a challenge for video semantic content analysis.The performance of semantic concept detection methods depends on modeling and matching the video semantic content exactly.In this research,perception concept and semantic concept were defined to Abstract and model video semantic content.Furthermore,the knowledge-assisted framework for semantic concept detection was proposed,in which the context knowledge was modeled using ontology,and the semantic concepts were detected by combining with low-level features and context information.Finally,the linear fusion strategy was used to fuse the matching results and detect the semantic concepts.The proposed method was demonstrated in a news video domain and shows promising results.