A hierarchical semantic associative video model was proposed which described video information in hierarchical concept tree, scene network and semantic object net.
提出一种视频的分层语义联想模型，构造三个层次的信息：概念层次树，场景网络和语义对象网络。
According to the MPEG-4 verification model, video sequence must be segmented into semantic video objects. Their motion, shape and texture information are coded respectively.
按照MPEG - 4的校验模型，视频序列必须先分割成具有语义意义的视频对象，然后对其运动、形状和纹理分别进行编码。
The method of SVM is used to train a large amount of pictures to obtain the model which is used to detect the semantic of consecutive video frames.
采用支持矢量机的方法先对大量的图像进行训练，然后对连续的视频帧进行了语义探测。
The authors mainly discussed OVSR's ontology structure, video semantic model and indexing model, and studied the user's searching rewriting algorithm and ontology reasoning algorithm.
主要论述OVSR的本体架构，视频语义模型和索引模型，研究OVSR的查询重写算法以及本体推理算法。
The authors mainly discussed OVSR's ontology structure, video semantic model and indexing model, and studied the user's searching rewriting algorithm and ontology reasoning algorithm.
主要论述OVSR的本体架构，视频语义模型和索引模型，研究OVSR的查询重写算法以及本体推理算法。
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