Unsupervised-Texture..

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Transcript Unsupervised-Texture..

Unsupervised Texture
Segmentation on Multi-core
Hardware
Chris White
Motivation
Algorithm
Create feature vectors that captures
“local structure” of image
Smooth feature vectors while
preserving region boundaries
Cluster vectors into regions of similar
texture
Feature Vectors
Capture “local structure”
Structure Tensor
Smoothing
Blur feature vectors, but maintain
region boundaries
Solve the diffusion equation
Explicit vs. Implicit solution?
Clustering similar feature
vectors into regions
Looking at k-means and a special case
of the level set
Both algorithms have non-uniform
reduction problem on graphics
hardware
Non-uniform Reduction
Find sum of subset of pixels in image
Create null
records outside
of region then
sum all pixels
Current Status
Have slightly buggy end-to-end GPU
prototype using K-means for the
clustering stage
Can process small images (e.g.
255x255) at about 10 FPS
Preliminary Results
Short Term Tasks
Work on implicit solution to diffusion
equation

This has both accuracy and efficiency
implications
Finish CPU equivalent program
Work on level set
Work on creating features at multiple
scales
Long Term Research
Port app to the still-under-construction
API for multi-core chip being developed
by U.Va’s larger architecture research
group