Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/13426
Title: Content-based image retrieval in P2P networks with bag-of-features
Authors: Zhang, L
Wang, Z
Feng, D
Keywords: Bag-of-Features
Image retrieval
Peer-to-peer
Issue Date: 2012
Publisher: IEEE
Source: 2012 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 9-13 July 2012, Melbourne, VIC, p. 133-138 How to cite?
Abstract: Recently, the Bag-of-Features (BoF) model has emerged as a popular solution to scalable content-based image retrieval (CBIR), due to great success of the Bag-of-Words (BoW) model in textual information processing. While most of the existing algorithms on CBIR in P2P networks focus on indexing high dimensional low level features, we propose to address such an issue by employing the BoF model. However, it is not straightforward due to the fact that the BoF model depends on a global codebook and it is very challenging to create and maintain such a global codebook across the whole P2P network. We design a novel online sampling mechanism to create a codebook with low network cost. Since the number of features in each image is large, compared to a text query generally consisting of several keywords, information exchange between nodes for each query image generates high network cost. In order to further reduce the network cost, we implement two static index pruning policies to limit the document length and the returned term weights. Our comprehensive experimental results show that our proposed approach is able to scale up to medium size networks with performance comparable to the centralized environment.
URI: http://hdl.handle.net/10397/13426
ISBN: 978-1-4673-2027-6
DOI: 10.1109/ICMEW.2012.30
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

4
Last Week
1
Last month
Citations as of Oct 17, 2017

WEB OF SCIENCETM
Citations

3
Last Week
0
Last month
Citations as of Oct 18, 2017

Page view(s)

34
Last Week
2
Last month
Checked on Oct 23, 2017

Google ScholarTM

Check

Altmetric



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.