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Performance Evaluation of Near-duplicate Web Image Retrieval Algorithm of Person Images

LUO Yumei,WANG Rui   

  1. Faculty of Compute Information,Kunming Metallurgy College,Kunming 650033,China
  • Received:2018-05-10 Online:2018-06-30 Published:2018-06-30

Abstract: Recent studies have revealed that numerous near-duplicate Web images can be used as an intermediate step to implement some traditional difficult compute rvision tasks.This paper presents a comprehensive study of the existing near-duplicate image retrieval methods in a structural way.Four representatives of the existing methods,i.e.hash signature,meanSSIM,BoVW  with SIFT features and ARG,are experimentally evaluated using a self-constructed data set containing 24762 images.The experimental results reveal that compared with global feature based methods,local feature based ones are usually more appropriate for the task of person identification in web images,as they can deal with partial duplicate and scene similar images better.In particular,BoVW  with SIFT features is recommended as it provides the best trade-offbetween on-line speed and retrieval accuracy.

Key words: retrieval, Web images, algorithm, evaluation

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