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PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Pixel Aligned Warping for Multiprojector Tiled Displays Mark Hereld and Rick Stevens Argonne National.

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Presentation on theme: "PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Pixel Aligned Warping for Multiprojector Tiled Displays Mark Hereld and Rick Stevens Argonne National."— Presentation transcript:

1 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Pixel Aligned Warping for Multiprojector Tiled Displays Mark Hereld and Rick Stevens Argonne National Laboratory Computation Institute University of Chicago

2 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Introduction  Warping image content into projector frame buffers is a fact of life  Driven by geometrical constraints  Never driven by clarity constraint  except in that geometrical constraints are sometimes driven by alignment with nearby or overlapping projected content  What if content crispness is more important?

3 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Pixel Exploit  Nyquist and the pixel  Lone illuminated pixel contains high frequency components well beyond Nyquist cutoff  Anti-aliasing techniques are the standard antidote when sharp features don’t fall on pixel boundaries  Often exploited to represent thin, crisp features  Graphics: single pixel width horizontal and vertical lines, and points  Text: sharp and sometimes small fonts

4 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Example

5 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Warped

6 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Nearest Neighbor Plate Rift Line

7 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Warped w/Rifts

8 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Detail

9 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Possible Approaches  Modified nearest neighbor: soften rift boundary  Stretch rift lines to avoid cutting through important stuff  Perturb warp according to local measure of steepness  Minimize an energy function that includes terms reflecting affinity of features for pixel boundaries and gives weight to keeping proximal features together  Crystallize pixel values around nucleation centers related to locations of high-contrast features in the image  Segment the image into unwarpable islands of content X coordinate of pixel plate rift dX of warp

10 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Possible Approaches  Modified nearest neighbor: soften rift boundary  Stretch rift lines to avoid cutting through important stuff  Perturb warp according to local measure of steepness  Minimize an energy function that includes terms reflecting affinity of features for pixel boundaries and gives weight to keeping proximal features together  Crystallize pixel values around nucleation centers related to locations of high-contrast features in the image  Segment the image into unwarpable islands of content

11 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Possible Approaches  Modified nearest neighbor: soften rift boundary  Stretch rift lines to avoid cutting through important stuff  Perturb warp according to local measure of steepness  Minimize an energy function that includes terms reflecting affinity of features for pixel boundaries and gives weight to keeping proximal features together  Crystallize pixel values around nucleation centers related to locations of high-contrast features in the image  Segment the image into unwarpable islands of content

12 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Possible Approaches  Modified nearest neighbor: soften rift boundary  Stretch rift lines to avoid cutting through important stuff  Perturb warp according to local measure of steepness  Minimize an energy function that includes terms reflecting affinity of features for pixel boundaries and gives weight to keeping proximal features together  Crystallize pixel values around nucleation centers related to locations of high-contrast features in the image  Segment the image into unwarpable islands of content x,y u,v f 0u,f 0v C i-1. C i C i. C i+1 k kk feature blocking energy target warp term pixel mis-alignment penalty f u,f v

13 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Possible Approaches  Modified nearest neighbor: soften rift boundary  Stretch rift lines to avoid cutting through important stuff  Perturb warp according to local measure of steepness  Minimize an energy function that includes terms reflecting affinity of features for pixel boundaries and gives weight to keeping proximal features together  Crystallize pixel values around nucleation centers related to locations of high-contrast features in the image  Segment the image into unwarpable islands of content

14 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Possible Approaches  Modified nearest neighbor: soften rift boundary  Stretch rift lines to avoid cutting through important stuff  Perturb warp according to local measure of steepness  Minimize an energy function that includes terms reflecting affinity of features for pixel boundaries and gives weight to keeping proximal features together  Crystallize pixel values around nucleation centers related to locations of high-contrast features in the image  Segment the image into unwarpable islands of content

15 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Islands in the Ocean  Lock contiguous blocks of high contrast pixels, islands, to one another and to nearest plate  Warp everything else, the ocean, in the usual fashion  Don’t worry about possible artifacts around the edges of the islands, the beaches

16 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Algorithm  Compute contrast of each pixel  w.r.t. 3x3 neighborhood  Binarize  Consolidate into islands  Morphological fill & open  Pin island coordinates  to plate containing island centroid  Warp ocean  Transfer islands into warped ocean  cut-and-paste unwarped

17 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Example

18 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Contrast

19 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Labeled

20 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Labeled w/Rifts

21 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC PAW

22 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Warped

23 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Results  Interesting notion  Simple algorithm  Islands in the Ocean  Very effective  Except when it’s not See “Weaknesses”  Large warps  Rotation  Keystone  Tiling introduces new problems  Overlap or abutting  Large islands  Collisions StrengthsWeaknesses

24 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Future  Robust rules for handling pathological cases gracefully  Fast implementation  compatible with hardware accelerators  Handle blending areas in tiled displays  Awareness of horizontal and vertical features  allow lines to stretch or shrink but not kink  Apply to image scaling  Particularly high res laptop display driving XGA projector

25 PROCAMS 2005 San Diego Futures Laboratory MCS ANL CI UC Summary  Pixel edges are commonly exploited to represent sub-Nyquist features  Warping can degrade this crispness  Many approaches to pixel aligned warping that could preserve much of this crispness at the expense of geometrical accuracy  Islands in the Ocean is effective


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