Title
Client-Side Relevance Feedback Approach For Image Retrieval In Mobile Environment
Abstract
During the last decade, high quality (i.e. over 1 megapixel) built-in cameras have become standard features of handheld devices. Users can take high-resolution pictures and share with friends via the internet. At the same time, the demand of multimedia information retrieval using those pictures on mobile devices has become an urgent problem to solve, and therefore attracts attention. A relevance feedback information retrieval process includes several rounds of query refinement, which incurs exchange of images between the mobile device and the server. With limited wireless bandwidth, this process can incur substantial delay, making the system unfriendly to use. This issue is addressed by considering a Client-side Relevance Feedback (CRF) technique. In the CRF system, Relevance Feedback (RF) is done on client side along. Mobile devices' battery power is saved from exchanging images between server and client and system response is instantaneous, which significantly enhances system usability. Furthermore, because the server is not involved in RF processing, it is able to support more users simultaneously. The experiment indicates that the system outperforms the traditional server-client relevance feedback systems on the aspects of system response time, mobile battery power saving, and retrieval result.
Publication Date
2-28-2013
Publication Title
Multimedia Data Engineering Applications and Processing
Number of Pages
193-204
Document Type
Article; Book Chapter
Personal Identifier
scopus
DOI Link
https://doi.org/10.4018/978-1-4666-2940-0.ch010
Copyright Status
Unknown
Socpus ID
84944674892 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84944674892
STARS Citation
Yu, Ning; Hua, Kien A.; and Liu, Danzhou, "Client-Side Relevance Feedback Approach For Image Retrieval In Mobile Environment" (2013). Scopus Export 2010-2014. 6686.
https://stars.library.ucf.edu/scopus2010/6686