PhotoMesa A Zoomable Image Browser Using Quantum Treemap and Bubblemap

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PhotoMesa A Zoomable Image Browser Using Quantum Treemap and Bubblemap

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PhotoMesa. A Zoomable Image Browser Using. Quantum Treemap and Bubblemap. Presented by Khanh-Dung (KD) Nguyen ... ( no custom albums) The Heart of PhotoMesa ' ... –

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Title: PhotoMesa A Zoomable Image Browser Using Quantum Treemap and Bubblemap


1
PhotoMesaA Zoomable Image Browser Using Quantum
Treemap and Bubblemap
  • Presented by Khanh-Dung (KD) Nguyen
  • COSC 686 Information Visualization
  • Instructor Dr. Harry Hochheiser
  • 02/27/2007

2
Introduction
  • Information retrieval systems for
    multimediaimages
  • 2001 queries for items of interest
  • Need good interface, visualization interaction
    techniques
  • Importance
  • Need for browsing of search results, (no grids of
    thumbnails, scroll bars)
  • Pleasure spontaneity. (no custom albums)

3
The Heart of PhotoMesa
  • I wanted to concentrate on the images and more
    importantly, as I was looking at the photos with
    my daughter, it was crucial that she be an active
    part of the interaction, and not just a passive
    bystander.
  • Benjamin B. Bederson

4
Related Works
  • PhotoFinder - polished traditional approach
  • Document Lens 2D Fisheye view - single
    view at a time
  • AutoAlbum automatically cluster photos -
    scrolling
  • Personal Digital Historian co-present
    use - multiple images interaction
  • ZoomBrowser EX ZUIs
  • Pad - one sized directories
    ? unreadable

5
Design Goals
  • Simple to use
  • Work well for family-use settings
  • Support collections of photos, efficient use
    of screen space.

6
New Algorithms
  • Quantum treemap
  • Treemap produces proportional areas of 2D space
    according to requested list
  • Quantum indivisible contents
  • Bubblemap
  • Generates non-rectangular groups (of images)

7
Quantum Treemap
  • Stable aspect ratio
  • Grow horizontally / vertically
  • ? best matches aspect ratio
  • Stopping conditions
  • Regular
  • Quad 2x2 rectangles
  • Snake sequential lay-out
  • Pivot selection
  • try all 3 lay-outs (middle, largest or smallest
    element ? closest to equal size

8
Quantum vs. Ordered Treemap
9
Bubblemap
  • Minimum unused space
  • Good with pre-clustered high-dimensional set of
    relationships
  • Fast O(n) run time
  • ? Could be hard to parse visually

10
Future Work
  • Integration with PhotoFinder other metadata
  • Deployment with different modalities (stand-alone
    CDs, integration with the Web)
  • Detailed user study for effectiveness
    efficiency.

11
References
  • Balabanovic, M., Chu, L. L., Wolff, G. J.
    (2000). Storytelling with Digital Photographs. In
    proceedings of Human Factors in Computing Systems
    (CHI 2000) ACM Press, pp.564-571.
  • Kang, H., Schneiderman, N. (2000).
    Visualization Methods for Personal Photo
    Collections Browsing and Searching in the
    PhotoFinder. In Proceedings of IRRR International
    Conference on Multimedia and Expo (ICME2000) New
    York IEEE, pp. 1539-1342.
  • Platt, J. (2000). AutoAlbum Clustering Digital
    Photographs Using Probabalistic Model Merging. In
    Proceedings of IEEE Workshop on Content-based
    Access of Image and Video Libraries (CBAIVL-2000)
    IEEE Press
  • Robertson, G. G., Mackinlay, J. D. (1993). The
    Document Lens. In Proceedings of User Interface
    and Software Technology (UIST 93) ACM Press,
    pp.101-108.
  • Shen, C. Moghaddam, B., Lesh, N., Beardsley, P.
    (2001). Personal Digital Historian User
    Interface Design. In Proceedings of Extended
    Abstracts of Human Factors in Computing Systems
    (CHI 2001) ACM Press

12
Discussion
  • Questions?
  • Thoughts?
  • Comments?
  • Thanks!
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