为了提高对Web动画素材的组织、管理,该文提出了基于文本特征和视觉特征融合的Web动画素材标注算法。首先利用自动提取的Web动画素材上下文信息,结合Web动画素材名称、页面主题、URL以及ALT等属性组成特征集,提取出文本关键字;然后利用视觉与标注字之间的相关性,对自动提取的标注字进行过滤,实现Web动画素材的自动标注。实验表明该文提出的基于文本特征和视觉特征融合的Web动画素材标注算法可有效地应用于Web动画素材自动标注。
Abstract
In order to improve the management of web animation materials, a senmantic annotation algorithm based on fusion of text and visual features is proposed for web animation material. The context information of the animation material is first extracted, including its title, page caption, URL, ALT features. Then the candidate textual keywords are extracted by using WordNet semantic dictionary. We filter the annotation words by their correlation to the visual features. Finally, we build the semantic network over textual keywords and visual features to realize automatic annotation. Experiments show that the algorithm proposed in this paper can be effectively used in extracting semantic information from web animation material.
关键词
Web动画素材 /
文本特征 /
视觉特征 /
语义标注
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Key words
web animation material /
text feature /
visual feature /
semantics annotation
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参考文献
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脚注
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基金
中央高校基本科研业务费专项基金(DL10CB01),黑龙江省留学归国科学基金(LC2012C06),哈尔滨市科技创新人才专项基金(2012RFLXG022),东北林业大学研究生论文资助项目。
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