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+
Speed Up Texture Classification
in Clothing Retrieval System
電機三 吳瑋凌
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+What is clothing retrieval system?When a clothing image comes,
we’d like to find the same pictures or the similar ones.
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+What’s the data in images?
HOGLBPColor HistogramColor MomentSkin
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+Motivation
Large scale computing efficiency
=> want to find a way to speed up the system
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+MethodFind some conditions to classify
imagesOnly need to compute features with
those in the same class
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+Experiment
Use HOG to classify different texturesDefine 5 groups and use 25 training
pictures for each
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+HOG(Histogram of oriented gradients )Detect the edge of items Judge clothing texture 3*3*9=81 dimensions
z
cellblock
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+How to find conditions
threshold
Find a threshold making the precision high enough after splitting
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+How to find conditions
Don’t define threshold
Threshold=(max1+min2)/2
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+ExperimentOne dimension at most 10 threshold
valuesFind the one having the max precision
in all dimensions Set Paim
<threshold >threshold
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+ClasstreePaim=0.
7
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+Results5 pictures for each group(total=25
pictures)Calculate precision and recall for each
group
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+DiscussionThe relationship of P,R and PaimThe higher Paim, the higher P and R
Paim
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+DiscussionUse F1 to evaluate F1=2*P*R/(P+R)
Paim
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+DiscussionThe relationship of training time and
PaimThe higher Paim, the longer training
time
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+Conclusion
We can find some more important entry to classify some groups
Then we can only compute features of query image with those in the same groups
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+Thanks for your listening :)