#StackBounty: #classification #scikit-learn #computer-vision #preprocessing #dimensionality-reduction Reducing the size of a dataset

Bounty: 100

I am trying to classify gestures. I am using Python’s scikit learn library classification algorithms for that. I have collected depth images for this purpose. 200 samples are collected for each gesture. Each gesture is made up of 25 frames and each frame is of size 240×420. I tried PCA for dimensionality framewise for reducing the size of each gesture (200 samples each) to make it easy to run on the machine. Still the large size of the data make it difficult to run in my machine when the number of gestures to classify are larger than 4. I am looking for methods to make it run on my machine.


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