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Jigsaw Image Mosaics

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Title: Jigsaw Image Mosaics


1
Jigsaw Image Mosaics
  • Junhwan Kim, Fabio Pellacini
  • (Cornell University)
  • Siggraph 2002

2
What is it?
3
What does it do?
  • The Jigsaw Image Mosaic (JIM) algorithm takes
    as input an arbitrarily-shaped container image
    and a set of image tiles of arbitrary shape and
    generates a mosaic.
  • It then packs the container as compactly as
    possible with tiles of similar color to the
    container taken from the input set while
    optionally deforming them slightly to achieve a
    more visually-pleasing effect.

4
Related work (1)
  • Photomosaics square tiles on a rectangular
    grid.
  • Silvers, Hawley, 1997 Finkelstein, Range 1998

5
Related work (2)
  • Simulated Decorative Mosaics square tiles with
    varying orientations.
  • Hausner 2001

6
Related work (3)
  • Regular tiling with slight distortions of tile
    shapes. Kaplan, Salesin 2000
  • Random positions of tiles, gaps filled with
    samples from original image. Haeberli 1990
  • Packing problem (NP-hard) heuristics. Downsland
    1995, Milenkovic 1999

7
The problem
  • Given an arbitrarily-shaped container image and
    a set of arbitrarily-shaped tiles Ti, find a
    set of shapes Sj such that
  • the union over the Sj resembles the container
    image as closely as possible and
  • each Sj is a translated and rotated copy of one
    of the Ti, possibly incorporating a small
    deformation.

8
Energy minimization framework
(Color, Gap, Overlap, Deformation)
9
The algorithm-overview
  • Prepare and segment images using active contours.
    Kass 1987
  • Place tiles roughly, ignoring deformation
    (packing).
  • Refine placement of tiles and deform if
    necessary.
  • Assemble the final image.

10
The algorithm
11
Packing (1)
  • Place tiles one by one, ignoring the deformation
    term, such that the energy is minimized, and the
    tile is aligned to the container boundary.

12
Packing (2)
  • Place tiles until the container is full. If
    there is no suitable tile, backtrack to the last
    minimal energy configuration.

13
Refining
  • Use active contours whose vertices are subject
    to forces that maintain the initial shape,
    repulse two penetrating contours and attract two
    contours separated by a gap.

14
Optimizations (1)
  • Packing use centroidal Voronoi diagrams with
    sites the size of the medium tile size, and
    always pick a site with the minimal number of
    neighbors.

15
Optimizations (2)
  • Branch-and-bound with look-ahead to reduce
    backtracking overhead, penalize tiles that would
    make it harder to fill the container in the next
    iteration favor tiles with a small area and
    short circumference.
  • Container cleanup separate fragments shallower
    than the shallowest tile.

16
Optimizations (3)
  • Geometric hashing create a grid of squares
    representing hash table entries, then for each
    possible position and orientation of a tile,
    record the tile in the hash table.

17
Results
18
(No Transcript)
19
(No Transcript)
20
Summary
  • General energy-based framework.
  • New kind of mosaic.
  • Effective algorithm.
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