• DocumentCode
    130919
  • Title

    Quick search algorithms based on ethnic facial image database

  • Author

    BaoWei Hou ; Rui Zheng ; GuoSheng Yang

  • Author_Institution
    Dept. of Inf. Eng., Minzu Univ. of China, Beijing, China
  • fYear
    2014
  • fDate
    27-29 June 2014
  • Firstpage
    573
  • Lastpage
    576
  • Abstract
    The current popular image features index structure can be divided into tree-based structures, hash-based structures and machine learning based structures. In face recognition, selecting the appropriate image feature indexing structure to achieve large-scale face image matching has aways been a problem. In this paper, we present a global image features indexing method based on complete binary tree, using the ethnic facial image database, by contrast with the local sensitive hash(LSH), and principal component analysis (PCA) is adopted to extract facial image features for convienent. Experimental results show that the proposed method is superior to the local sensitive hashing in velocity.
  • Keywords
    database indexing; face recognition; feature extraction; image matching; learning (artificial intelligence); principal component analysis; tree data structures; visual databases; LSH; PCA; complete binary tree; ethnic facial image database; face recognition; facial image feature extraction; global image feature indexing method; hash-based structures; image feature indexing structure; large-scale face image matching; local sensitive hash; machine learning based structures; principal component analysis; tree-based structures; Binary trees; Face; Feature extraction; Indexing; Principal component analysis; Vectors; Vegetation; LSH; PCA; complete binary tree; global features;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2327-0586
  • Print_ISBN
    978-1-4799-3278-8
  • Type

    conf

  • DOI
    10.1109/ICSESS.2014.6933633
  • Filename
    6933633