Computer Science ›› 2018, Vol. 45 ›› Issue (5): 15-23.doi: 10.11896/j.issn.1002-137X.2018.05.003

Previous Articles     Next Articles

Advances in Image Reranking

ZHAO Xiao-yan, LIU Hong-zhe, YUAN Jia-zheng and YANG Shao-peng   

  • Online:2018-05-15 Published:2018-07-25

Abstract: In recent years,with the rapid development of Internet technology and the popularity of multimedia terminals electronic products,improving the efficiency of image search is a challenge in the media retrieval.The research of image search is a hot issue in the field of image.At present,many current commercial image search techniques have been applied,but the search results cannot meet the needs of users because of the existence of “semantic gap”.The search results still have some noise.Image search reordering is helpful to solve this problem.Based on the initial search,results can be more accurate and more abundant after reranking.In this paper,the research progress of image search reranking technology was introduced,and the current research methods were summarized and analyzed.The advantages and disadvantages of these methods and the key technologies in recent years were compared.The latest research progress and the future development of image search reranking and the future development were also given.

Key words: Image search,Reranking,Clustering,Classification,Map

[1] DENG L Q,HAO X N,XIA M,et al.Image Annotation by Similarity Content-based Image Retrieval[J].Computer Science 2014,41(11A):119-122.(in Chinese) 邓莉琼,郝向宁,夏鸣,等.基于内容检索的图像自动标注方法研究[J].计算机科学,2014,1(11A):119-122.
[2] SMEULDERS A W M,WORRING M,SANTINI S,et al.Content-based image retrieval at the end of the early years[J].IEEE Transactions on Pattern Analysis & Machine Intelligence,2000,22(12):1349-1380.
[3] ZHU J L,YANG X P,PENG L Q.Research on Effect of Adding Internal Semantic Relationship into Text Categorization[J].Computer Science,2016,43(9):82-86.(in Chinese) 朱建林,杨小平,彭鲸桥.融入内部语义关系对文本分类的影响研究[J].计算机科学,2016,3(9):82-86.
[4] WANG Y H,CHEN X R.Improved Text Clustering Algorithm Based on Kolmogorov Complexity [J].Computer Science,2016,43(5):243-246.(in Chinese) 王有华,陈笑蓉.基于Kolmogorov复杂性的文本聚类算法改进[J].计算机科学,2016,3(5):243-246.
[5] ZHANG J,LI D Y,WANG S G,et al.Multi-label Text Classification Based on Robust Fuzzy Rough Set Model [J].Computer Science,2015,2(7):270-275.(in Chinese) 张晶,李德玉,王素格,等.基于稳健模糊粗糙集模型的多标记文本分类[J].计算机科学,2015,2(7):270-275.
[6] LEE K S,PARK Y C,CHOI K S.Re-ranking model based on document clusters[J].Information Processing & Management,2001,37(1):1-14.
[7] CAO Z,QIN T,LIU T Y,et al.Learning to rank:from pairwise approach to listwise approach[C]∥Machine Learning,Procee-dings of the Twenty-Fourth International Conference.2007:129-136.
[8] ZLOOF M M.Query-by-Example:A data base language[J].Ibm Systems Journal,1977,16(4):324-343.
[9] ZLOOF M M.Query-by-example:the invocation and definition of tables and forms[C]∥International Conference on Very Large Data Bases,Framingham,Massachusetts,USA.1975:1-24.
[10] BOGERS T,BOSCH V A.Authoritative re-ranking in fusingauthorship-based subcollection search results[C]∥Belgian-Dutch Information Retrieval Workshop,Dir.2006:49-55.
[11] YAMAMOTO T,NAKAMURA S,TANAKA K.Rerank-by-Example:Efficient Browsing of Web Search Results[M]∥Database and Expert Systems Applications.Springer Berlin Heidelberg,2007:801-810.
[12] ROHINI U,VARMA V.A Novel Approach for Re-Ranking of Search Results Using Collaborative Filtering[C]∥Computing:Using Collaborative Filtering.International Conferenceon Computing:Theory and Applications.2007:491-496.
[13] YANG J G,FREDERKING Y,ROBERT E,et al.Translingual Information Retrieval:A Comparative Evaluation[C]∥ Procee-dings of the 15th International Joint Conference on ArtificialIntelligence.1997:708-715.
[14] YAN R,HAUPTMANN A,JIN R.Multimedia search withpseudo-relevance feedback[J].Lecture Notes in Computer Scien-ce,2003,2728:238-247.
[15] YAN R,HAUPRMANN A.Query expansion using probabilistic local feedback with application to multimedia retrieval[C]∥Sixteenth ACM Conference on Information and Knowledge Ma-nagement(CIKM 2007).Lisbon,Portugal,November,2007:361-370.
[16] HSU W H,KENNEDY L S,CHANG S F.Video search reran-king via information bottleneck principle[C]∥ACM International Conference on Multimedia.Santa Barbara,CA,USA,2006:35-44.
[17] BEN-HAIM N,BABENKO B,BELONGIE S.Improving Web-based Image Search via Content Based Clustering[C]∥Confe-rence on Computer Vision and Pattern Recognition Workshop.IEEE Computer Society,2006:106.
[18] BEN-HAIM N,BABENKO B,BELONGIE S.Improving Web-based Image Search via Content Based Clustering[C]∥Confe-rence on Computer Vision and Pattern Recognition Workshop.IEEE Computer Society,2006:106.
[19] PARK G,BAEK Y,LEE H K.Re-ranking algorithm using post-retrieval clustering for content-based image retrieval[J].Information Processing & Management,2005,41(2):177-194.
[20] VAN LEUKEN R H,GARCIA L,et al.Visual diversification of image search results[C]∥International Conference on World Wide Web(WWW 2009).Madrid,Spain,2009:341-350.
[21] FERGUS R,PERONA P,ZISSERMAN A.A Visual Category Filter for Google Images[M]∥Computer Vision-ECCV 2004.Springer Berlin Heidelberg,2004:242-256.
[22] BRIN S,PAGE L.The anatomy of a large-scale hypertextualWeb search engine [J].Computer Networks & Isdn Systems,1998,30(1-7):107-117.
[23] HSU W H.Video search reranking through random walk over document-level context graph[C]∥International Conference on Multimedia 2007.Augsburg,Germany,2007:971-980.
[24] BALUJA S,SETH R,SIVAKUMAR D,et al.Video suggestion and discovery for youtube:taking random walks through the view graph[C]∥Proceedings of the 17th International Confe-rence on World Wide Web.ACM,2015:895-904.
[25] JING Y,BALUJA S.VisualRank:applying PageRank to large-scale image search[J].IEEE Transactions on Pattern Analysis &Machine Intelligence,2008,30(11):1877-1890.
[26] TIAN X,YANG L,WANG J,et al.Bayesian video searchreranking[C]∥International Conference on Multimedia 2008.Vancouver,British Columbia,Canada,2008:131-140.
[27] HOU H M,XU X S,WANG G,et al.Joint-Rerank:a novel method for image search reranking[J].Multimedia Tools & Applications,2012,74(4):1423-1442.
[28] LU J,ZHOU J,WANG J,et al.Image search results refinement via outlier detection using deep contexts[C]∥IEEE Conference on Computer Vision & Pattern Recognition.2012:3029-3036.
[29] GAO S,CHENG X,WANG H,et al.Concept model-based unsupervised web image re-ranking[C]∥IEEE International Conference on Image Processing.IEEE Press,2009:793-796.
[30] KENNEDY L S,CHANG S F.A reranking approach for con-text-based concept fusion in video indexing and retrieval[C]∥ACM International Conference on Image and Video Retrieval,Civr 2007.2007:333-340.
[31] NATSEV A,HAUBOLD A,JELENA,et al.Semantic concept-based query expansion and re-ranking for multimedia retrieval[C]∥Proceedings of the 15th International Conference on Multimedia.ACM,2007:991-1000.
[32] LIU Y,MEI T,HUA X S,et al.Learning to video search rerank via pseudo preference feedback[C]∥IEEE International Confe-rence on Multimedia and Expo.2008:297-300.
[33] YAO T,MEI T,NGO C W.Co-reranking by mutual reinforcement for image search[C]∥ACM International Conference on Image and Video Retrieval(Civr 2010).Xi’an,China,2010:34-41.
[34] YAN R,HAUPTMANN A G.Co-retrieval:A Boosted Reran-king Approach for Video Retrieval[J].IEEE Proceedings of Vision Image and Signal Processing,2004,19(5):888-895.
[35] LIU Y,MEI T,HUA X S.Crowd Reranking:Exploring Multiple Search Engines for Visual Search Reranking[C]∥International ACM SIGIR Conference on Research and Development in Information Retrieval(SIGIR 2009).Boston,MA,USA,2009:500-507.
[36] KENNEDY L S,CHANG S F.A reranking approach for con-text-based concept fusion in video indexing and retrieval[C]∥ACM International Conference on Image and Video Retrieval,Civr 2007.Amsterdam,the Netherlands,2007:333-340.
[37] XU X L,ZHANG L B,LIU X D,et al.Image Retrieval Relevance Feedback Algorithm Based onarticle Swarm Optimization[J].Acta Electronica Sinica,2010,38(8):1935-1940.
[38] DENG C,JI R,TAO D,et al.Weakly Supervised Multi-Graph Learning for Robust Image Reranking[J].IEEE Transactions on Multimedia,2014,16(3):785-795.

No related articles found!
Full text



[1] . [J]. Computer Science, 2018, 1(1): 1 .
[2] LEI Li-hui and WANG Jing. Parallelization of LTL Model Checking Based on Possibility Measure[J]. Computer Science, 2018, 45(4): 71 -75, 88 .
[3] XIA Qing-xun and ZHUANG Yi. Remote Attestation Mechanism Based on Locality Principle[J]. Computer Science, 2018, 45(4): 148 -151, 162 .
[4] LI Bai-shen, LI Ling-zhi, SUN Yong and ZHU Yan-qin. Intranet Defense Algorithm Based on Pseudo Boosting Decision Tree[J]. Computer Science, 2018, 45(4): 157 -162 .
[5] WANG Huan, ZHANG Yun-feng and ZHANG Yan. Rapid Decision Method for Repairing Sequence Based on CFDs[J]. Computer Science, 2018, 45(3): 311 -316 .
[6] SUN Qi, JIN Yan, HE Kun and XU Ling-xuan. Hybrid Evolutionary Algorithm for Solving Mixed Capacitated General Routing Problem[J]. Computer Science, 2018, 45(4): 76 -82 .
[7] ZHANG Jia-nan and XIAO Ming-yu. Approximation Algorithm for Weighted Mixed Domination Problem[J]. Computer Science, 2018, 45(4): 83 -88 .
[8] WU Jian-hui, HUANG Zhong-xiang, LI Wu, WU Jian-hui, PENG Xin and ZHANG Sheng. Robustness Optimization of Sequence Decision in Urban Road Construction[J]. Computer Science, 2018, 45(4): 89 -93 .
[9] LIU Qin. Study on Data Quality Based on Constraint in Computer Forensics[J]. Computer Science, 2018, 45(4): 169 -172 .
[10] ZHONG Fei and YANG Bin. License Plate Detection Based on Principal Component Analysis Network[J]. Computer Science, 2018, 45(3): 268 -273 .