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User-driven lossy compression for images and video

Conference Paper


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Abstract


  • In any given scene, a human observer is typically

    more interested in some objects than others, and will pay more attention

    to those objects they are interested in. This paper aims to

    capture this attention focusing behavior by selectively merging a

    fine-scale oversegmentation of a frame so that interesting regions

    are segmented into smaller regions than uninteresting regions.

    This results in a new type of image partitioning which reflects

    in the image the amount of attention we pay to a particular

    image region. This is done using a novel, interactive method for

    learning merging rules for images and videos based on defining

    a weighted distance metric between adjacent oversegments. We

    present as an example application of this technique a new lossy

    image and video stream compression method which attempts to

    minimize the loss in areas of interest.

Authors


  •   Brewer, Nathan (external author)
  •   Liu, Nianjun (external author)
  •   Cheng, Li (external author)
  •   Wang, Lei

Publication Date


  • 2009

Citation


  • Brewer, N., Liu, N., Cheng, L. & Wang, L. (2009). User-driven lossy compression for images and video. Proceedings of International Conference on Image and Vision Computing New Zealand (IVCNZ) (pp. 346-351). Australia: IEEE.

Scopus Eid


  • 2-s2.0-77951147060

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1611&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/605

Start Page


  • 346

End Page


  • 351

Abstract


  • In any given scene, a human observer is typically

    more interested in some objects than others, and will pay more attention

    to those objects they are interested in. This paper aims to

    capture this attention focusing behavior by selectively merging a

    fine-scale oversegmentation of a frame so that interesting regions

    are segmented into smaller regions than uninteresting regions.

    This results in a new type of image partitioning which reflects

    in the image the amount of attention we pay to a particular

    image region. This is done using a novel, interactive method for

    learning merging rules for images and videos based on defining

    a weighted distance metric between adjacent oversegments. We

    present as an example application of this technique a new lossy

    image and video stream compression method which attempts to

    minimize the loss in areas of interest.

Authors


  •   Brewer, Nathan (external author)
  •   Liu, Nianjun (external author)
  •   Cheng, Li (external author)
  •   Wang, Lei

Publication Date


  • 2009

Citation


  • Brewer, N., Liu, N., Cheng, L. & Wang, L. (2009). User-driven lossy compression for images and video. Proceedings of International Conference on Image and Vision Computing New Zealand (IVCNZ) (pp. 346-351). Australia: IEEE.

Scopus Eid


  • 2-s2.0-77951147060

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1611&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/605

Start Page


  • 346

End Page


  • 351