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	基于相关视觉关键词的图像自动标注方法研究; Automatic Image Annotation Based on Relevant Visual Keywords
	柯逍 ; 李绍滋 ; 曹冬林
	2012
关键词	图像自动标注 视觉关键词 自适应阈值 相关模型 抽象标注词 非抽象标注词 automatic image annotation visual keyword adaptive threshold relevance model Abstract annotation word non-Abstract annotation word
英文摘要	图像自动标注是计算机视觉与模式识别等领域中的重要问题.针对现有模型未对文本关键词的视觉描述形式进行建模,导致标注结果中大量出现与图像视觉内容无关的标注词等问题,提出了基于相关视觉关键词的图像自动标注模型VkrAM.该模型将标注词分为非抽象标注词与抽象标注词.首先建立非抽象标注词的视觉关键词种子,并提出了一个新方法抽取非抽象标注词对应的视觉关键词集合;接着根据抽象关键词的特点,运用提出的基于减区域的算法抽取抽象关键词对应的视觉关键词种子与视觉关键词集合;然后提出一个自适应参数方法与快速求解算法用于确定不同视觉关键词的相似度阈值;最后将上述方法相结合并用于图像自动标注中.该模型能从一定程度上解决标注结果中出现的大量无关标注词问题.实验结果表明,该模型在大多数指标上相比以往模型均有所提高.; Automatic image annotation is a significant and challenging problem in pattern recognition and computer vision areas.At present,existing models can not describe the visual representations of corresponding Keywords,which would lead to a great number of irrelevant annotations in final annotation results.These annotation words are not related to any part of images in visual contents.A new automatic image annotation model(VKRAM) based on relevant visual Keywords is proposed to overcome the above problems.Our model divides each keyword into two categories:Abstract word or non-Abstract word.Firstly,we establish visual keyword seeds of each non-Abstract word,and then a new method is proposed to extract visual keyword collections by using corresponding visual seeds.Secondly,according to the traits of Abstract words,an algorithm based on subtraction regions is proposed to extract visual keyword seeds and corresponding collections of each Abstract word.Thirdly,we propose an adaptive parameters method and a fast solution algorithm to determine the similarity thresholds of each keyword.Finally,the combinations of the above methods are used to improve annotation performance.Experimental results conducted on Corel 5K datasets verify the effectiveness of the proposed annotation image model and it has improved the annotation results on most evaluation methods.; 国家自然科学基金项目(60873179;60803078);高等学校博士学科点专项科研基金项目(20090121110032);深圳市科技计划研究项目(JC200903180630A;ZYB200907110169A)
语种	zh_CN
内容类型	期刊论文
源URL	[http://dspace.xmu.edu.cn/handle/2288/119823]
专题	数学科学－已发表论文
推荐引用方式 GB/T 7714	柯逍,李绍滋,曹冬林. 基于相关视觉关键词的图像自动标注方法研究, Automatic Image Annotation Based on Relevant Visual Keywords[J],2012.
APA	柯逍,李绍滋,&曹冬林.(2012).基于相关视觉关键词的图像自动标注方法研究..
MLA	柯逍,et al."基于相关视觉关键词的图像自动标注方法研究".(2012).

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