一种融合本体与条件随机场的视频语义提取方法

A Video Semantic Extraction Method Based on Fusion Ontology and Conditional Random Field

从时空角度结合条件随机场模型及本体概念,提出了一种视频语义特征提取方法,其中包括视频低层特征模型参数估计(model parameter estimation,MPE)算法和高层对象语义模型更新(model update,MU)算法。该方法可以实现视频语义概念本体的自动提取和标注,为语义特征提取及分析提供支持。实验结果表明,该方法提升了视频语义特征提取的精确率和召回率。

This paper proposes a video semantic feature extraction method from the perspective of time-space with conditional random domain model and ontology,which includes video low-level feature model parameter estimation(model parameter estima⁃tion,MPE)algorithm and high-level object semantic model update(model update,MU)algorithm.This method can realize the au⁃tomatic extraction and annotation of video semantic concept ontology.It can provide support for semantic feature extraction and analysis.The experiment’s results show that the method improves the precision and recall rate of video semantic feature extraction.