计算机科学 ›› 2014, Vol. 41 ›› Issue (5): 82-85.doi: 10.11896/j.issn.1002-137X.2014.05.018
许喆,陈福才,李邵梅,李星
XU Zhe,CHEN Fu-cai,LI Shao-mei and LI Xing
摘要： 为解决基于欧氏局部敏感哈希(E2LSH)的视觉词典法存在的内存消耗大、在图像背景明显变化时检索精度不高及增大数据库规模导致检索效率降低的问题,在采用多探寻LSH对特征点进行聚类的基础上提出的基于嵌入汉明码的单词映射链投票的图像检索方法。该方法首先采用多单词映射和软量化思想构造单表视觉词典,缩小词典规模以降低内存消耗；然后通过嵌入汉明码生成单词映射链,并提出一种权重赋予函数来增加检索精度；最后对匹配返回的单词映射链进行加权投票完成图像检索。实验结果表明,该方法能有效降低检索的内存消耗,提高检索精度,且适用于大规模数据库条件下的检索处理。
| [1] Lowe D G．Distinctive image features from scale-invariant keypoints[J]．International Journal of Computer Vision,2004,60(2):91-110 [2] Jurie F,Triggs B．Creating efficient codebooks for visual recognition[C]∥Proceedings of International Conference on ComputerVision．Beijing,2005:604-610 [3] Jegou H,Douze M,Schmid C．Hamming embedding and weak geometric consistency for large scale image search[C]∥IEEE Conference on European Conference on Computer Vision．Heidelberg,2008:1-29 [4] Philbin J,Chum O,Isard M,et al．Lost in quantization:improving particular object retrieval in large scale image databases[C]∥IEEE Conference on Computer Vision and Pattern Recognition．Anchorage,2009:278-286 [5] Nister D,Stewenius H．Scalable recognition with a vocabularytree [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition．New York,2006:2161-2168 [6] Philbin J,Chum O,Isard M,et al．Object retrieval with large vocabularies and fast spatial matching [C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition．Minneapolis,2007:1-8 [7] Cao Yang,Wang Chang-hu,Li Zhi-wei,et al．Spatial-bag-of-features[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition．San Francisco,USA,2010:3352-3359 [8] Zhao Yong-we,Li Bi-cheng,Peng Tian-qiang,et al．An Object Retrieval Method Based on Randomized Visual Dictionaries and Query Expansion[J]．Journal of Electronics & Information Technology,2012,34(5):1154-1161 [9] Gionis A,Indyk P,Motwani R．Similarity search in high dimensions via hashing[C]∥Proceedings of the 25th International Conference on Very Large Data Bases (VLDB)．Edinburgh,Scotland,1999:518-529 [10] Zhang Bo-lin,Wang Chun-heng,Xiao Bai-hua,et al．Image Representation Using Bag-of-phrases[J]．Acta Automatica Sinica,2012,38(1):46-54 [11] Phibin J,Chum O,Isard M,et al．Object retrieval with large vocabularies and fast spatial matching[C]∥Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition．Minneapolis,2007:1-8 [12] Sadeghi M A,Farhadi A．Recognition Using Visual Phrases[C]∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition．Providence,2011:20-25 [13] Datar M,Immorlica N,Indyk P,et al．Locality-sensitive hashing scheme based on p-stable distributions[C]∥Proceedings of the Twentieth Annual Symposium on Computational Geometry．Brooklyn,New York,2004:253-262 [14] Lv Q,Josephson W,Wang Z,et al．Multi-probe LSH:efficient indexing for high-dimensional similarity search[C]∥Procee-dings of the 33rd international conference on Very large data bases,VLDB’07．VLDB Endowment,2007:950-961 [15] Gao Hao-lin,Peng Tian-qiang,Li Bi-cheng,et al．A Fast Re-trieval Method Based on Frequent Items Voting of Multi Table and Bucket Map Chain[J]．Journal of Electronics & Information Technology,2012,34(11):2574-2581 [16] Wu X,Hauptmann A G,Ngo C W．Practical elimination of near-duplicates from web video search[C]∥Proceedings of the 15th International Conference on Multimedia．New York,USA:ACM Press,Sep 2007:218-227 [17] Jegou H,Douze M,Schmid C．Improving bag-of-features forlarge scale image search[J]．International Journal of Computer Vision,2010,87(3):316-336 [18] Robotics research group．Oxford dataset．http://www.robots.ox.ac.uk/_vgg/data/oxbuildings,2011-04-16 |
| No related articles found! |
|
||
首页