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基于Bayes的自动图像标注 被引量：1

Automatic Image Annotation Based on Bayes
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摘要 给出了一种基于Bayes的图像自动标注方法.将图像标注问题看做多类分类问题,通过判断类条件概率密度来选择最佳标注词,并在Corel图像库上进行了实验.实验验证了该方法的有效性. This paper gives a method of automatic image annotation based on Bayes image annotation which is considered as a problem of multi-class classifier, and the best annotation words are selected by judging class conditional possibility density. This method is tested on Corel image database, and the result proves its effectiveness.
作者 臧淼 张永梅 李金泉
机构地区 北方工业大学信息工程学院
出处 《北方工业大学学报》 2014年第1期7-9,64,共4页 Journal of North China University of Technology
基金 北京市教委科研计划面上项目 2013年国家级大学生科学研究计划项目(1302)
关键词 BAYES 自动图像标注 分类 Bayes automatic image annotation classification
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献9

  • 1鲍泓,徐光美,冯松鹤,须德.自动图像标注技术研究进展[J].计算机科学,2011,38(7):35-40. 被引量：22
  • 2Dygulu P,Bamard K,Freitas N,et al. Object rec- ognition as machine translation: learning a lexicon for a fixed image vocabularyEC~//Proc of Europe- an Conf on Computer Vision( ECCV~ 02 ), Copen- hagen, Denmark, 2002 .. 97-112.
  • 3Jeon J, Lavrenko V, Manmatha R. Automatic im- age annotation and retrieval using cross-media rel- evance models~C~ ///Proc of ACM SIGIR. ACM, 2003~119-126.
  • 4Xiang Y,Zhou X D, Liu Z T,et al. Semantic con- text modeling with maximal margin conditional random fields for automatic image annotationEC~ //Proc of IEEE Conference on Computer Vision and Pattern Recognition. San Francisco: IEEE, 2010.. 3368-3375.
  • 5Chang E,Goh K,Sychay G,et al. CBSA~ content-based so[t annotation for multimoda| image re- trieval using Bayes point machines E J 3. IEEE Trans on Circuits and Systems for Video Technol- ogy,2003.13(1) : 26-38.
  • 6Carneiro G,Chan A B, Moreno P J, et al. Super- vised learning of semantic classes for image anno ration and retrieval[J]. IEEE Transactions on Pat- tern Analysis and Machine Intelligence, 2007,29 (3) :394-410.
  • 7杨淑莹.模式识别与智能计算-Matlab技术实现[M].北京:电子工业出版社,2011:345-347.
  • 8纪颖.一种基于实例的图像自动语义标注方法[J].哈尔滨理工大学学报,2009,14(1):38-42. 被引量：4
  • 9Wang J Z, Li J, Wiederhold G. SIMPLicity: Se- mantics-sensitive integrated matching for picture libraries[-J~. IEEE Transactions on Pattern Analy- sis and Machine Intelligence, 2001,23 (9) : 947-963.

二级参考文献43

  • 1吴越聪.多媒体交叉参照检索和语义自动标注[D].杭州:浙江大学,2005.
  • 2HNANG J. Color-spatial Image Indexing and Applications[ D ]. New York, USA: Comell University, 1998:20 - 32.
  • 3HARALICK R M, SHANGMUGAM K. Texture Feature for Image Classification [ J ]. IEEE Transactions on Systems, 1973, SMC - 3(6) :768 -780.
  • 4龚坚.彩色图像分割和纹理分隔[D].南京:东南大学,1998.38-40.
  • 5WANG JAMES Z. SIMPLicity:Semantics-Sensitive Integrated Matching for Picture Libraries [ J ]. IEEE Transactions on Pattern Analysis and Machine Intelligence,2001,23(9) :947-963.
  • 6SOMERS H. Review Article: Example - based Machine Translation[J]. Machine Translation, 1999,14 (2) :113 - 157.
  • 7Cusano C, Ciocca G, Sehettini R. Image annotation using SVM [C] ff Proc. of Int. SPIE Conf. on Imaging IV. San Jose, CA, USA, Feb. 2004 : 330-338.
  • 8Lu Zhi-wu, Horace H S I, He Qi-zhen. Context-based multi-label image annotation [C]//Proceeding of the ACM International Conference on Image and Video Retrieval. Santorini, Fira, Greece, July 2009.
  • 9Maron O, Lozano-Perez T. Multiple-instance learning for natural scene elassification[C] // Proe. of Int. Conf. on Machine Learning (ICML'98). Madison,Wisconsin,USA,July 1998..341-349.
  • 10Yang C, Dong M, Fotouhi F. Region-based image annotation through multiple instance learning[C] //Proc, of ACM Conf. on Multimedia (ACM MM'05). Singapore,Nov. 2005:435 438.

共引文献26

同被引文献39

  • 1路晶,金奕江,马少平,茹立云.使用基于SVM的否定概率和法的图像标注[J].智能系统学报,2006,1(1):62-66. 被引量：2
  • 2芮晓光,袁平波,何芳,俞能海.一种新的基于语义聚类和图算法的自动图像标注方法[J].中国图象图形学报,2007,12(2):239-244. 被引量：9
  • 3Moil Y, Takahashi H, Oka R. Image - to - word transformation based on dividing and vector qiJJantizing images with words[C]. In MISRM'99 First International Workshop on Multimedia Intelligent Stor- age and Retrieval Management, 1999.
  • 4Duygulu P, Bamard K, Freitas N, D.A. Forsyth. Object recognition as machine translation: learning a lexicon for a fixed vocabulary [C]. Proceeding of European Conference. On Computer Vision (ECCV. 02). Copenhagen, Denmark, 2002: 97-112.
  • 5Jeon J, Lavrenko V, Manmatha R. Automatic image annotation and retrieval using cross - media relevance models [C]. Proc. of Int. ACM SIGIR Conf. on Research and Developmem in Information Re- trieval (ACM SIGIR. 03). Toronto, Canada, 2003: 119-126.
  • 6Dietterich T G, Lathrop R H, Lozano- P6rez T. Solving the multiple instance problem with axis - parallel rectangles [J]. Artificial Intelli- gence, 1997, 89 (1-2) 31-71.
  • 7Yang C, Dang M, Fotouhi F. Region- based image annotation through multiple instance learning [C]//roc. of ACM Conf. on Multimedia (ACM MM'05). Singapore, Nov. 2005: 435-438.
  • 8Tang J, Lewis P H. A study of quality issues for image auto - an - no- tation with the Corel dataset [J]. IEEE Trans. on Circuits and Sys- tems for Video Technology, 2007, 17 (3) : 384 - 389.
  • 9Cusmao C, Ciocea G, Schettini R. Image annotation using SVM [C] //Prec. of Int. SPIE Conf. on Imaging IV. San Jose, CA, USA, Feb. 2004: 330-338.
  • 10Cameiro G, Chan A B, Moreno P J, Vasconcelo N. Supervised Learning of Semantic Classes for Image Annotation and Retrieval [J]. IEEE Transactions On Pattern Analysis and Machine Intelligence, 2007, 29 (3): 394-410.

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二级引证文献4

北方工业大学学报
2014年 第1期

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