Fast Matting Using Large Kernel Matting Laplacian Matrices
Supplementary Materials
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Faster propagation 





input  trimap  r=1  r=17 
The propagation speed is much faster when we use a larger kernel. Notice that each iteration takes the same time in our algorithm (independent of r). A large kernel greatly reduces the whole running time due to fewer iterations. 
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KDtree trimap segmentation 



image 
segmented trimap 


Once the trimap is segmented, we solve the matte in each segment. This figure illustrates the order of solving the segments. The kernel size is adaptively set. (The outcome here is the Local Step 1 in our paper.) 
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High resolution results (Megapixel images) Images and trimaps are from the data set in www.alphamatting.com (Click the images to see the full size) 

7.6Mpixel image (3280*2310) (This is the high resolution version of Fig. 1 in our paper.) 
trimap 
closedform using coarsetofine 1359s 
ours 48s 
7.8Mpixel image (3355*2315) 
trimap 
closedform using coarsetofine 98s 
ours 10.0s 
5.4Mpixel image (2090*2600) 
trimap 
closedform using coarsetofine 273s 
ours 15.5s 
6.7Mpixel image (3173*2100) 
trimap 
closedform using coarsetofine 140s 
ours 11.1s 
7.6Mpixel image (2908*2600) 
trimap 
closedform using coarsetofine 218s 
ours 14.7s 