Skip to main content
placeholder image

Image compression and retrieval for Mobile Visual Search

Conference Paper


Abstract


  • Mobile Visual Search (MVS) is an emerging area

    of research given the explosion of smart and

    computationally powerful mobile devices. Typically, MVS

    involves the computation of local image features which are

    then used within a matching process. Such applications

    pose certain unique challenges due to computation, power

    and bandwidth constraints of the mobile device. This

    paper examines the trade-off between two general

    frameworks for implementing MVS: 1. sending

    compressed images and performing feature extraction and

    matching on a server; and 2. performing feature extraction

    on the mobile device and sending these to a server for

    matching. A number of local image feature algorithms are

    studied using various image compression schemes from the

    point view of matching accuracy and processing time.

    Results show that the matching accuracy of sending

    compressed images is comparable to sending compact

    image features when using a high quality image coder, in

    this case JPEG2000 and HDPhoto.

Publication Date


  • 2012

Citation


  • Y. Cao, C. H. Ritz & R. Raad, "Image compression and retrieval for Mobile Visual Search," in 2012 International Symposium on Communications and Information Technologies (ISCIT), 2012, pp. 1027-1032.

Scopus Eid


  • 2-s2.0-84872128282

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/310

Has Global Citation Frequency


Start Page


  • 1027

End Page


  • 1032

Place Of Publication


  • USA

Abstract


  • Mobile Visual Search (MVS) is an emerging area

    of research given the explosion of smart and

    computationally powerful mobile devices. Typically, MVS

    involves the computation of local image features which are

    then used within a matching process. Such applications

    pose certain unique challenges due to computation, power

    and bandwidth constraints of the mobile device. This

    paper examines the trade-off between two general

    frameworks for implementing MVS: 1. sending

    compressed images and performing feature extraction and

    matching on a server; and 2. performing feature extraction

    on the mobile device and sending these to a server for

    matching. A number of local image feature algorithms are

    studied using various image compression schemes from the

    point view of matching accuracy and processing time.

    Results show that the matching accuracy of sending

    compressed images is comparable to sending compact

    image features when using a high quality image coder, in

    this case JPEG2000 and HDPhoto.

Publication Date


  • 2012

Citation


  • Y. Cao, C. H. Ritz & R. Raad, "Image compression and retrieval for Mobile Visual Search," in 2012 International Symposium on Communications and Information Technologies (ISCIT), 2012, pp. 1027-1032.

Scopus Eid


  • 2-s2.0-84872128282

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/310

Has Global Citation Frequency


Start Page


  • 1027

End Page


  • 1032

Place Of Publication


  • USA