OpenCV + Artificial Neural Network
Translated text
I am trying to detect patterns in video images, for this I am using optical flow and collecting the movement of the pixels in a certain region and after that I want to train an MLP to recognize. I switched from digital image processing to digital signal processing.
These values refer to the displacement of each pixel, frame by frame.
When collecting the values of a video of 3 seconds, it returns about 5000 values. I have several videos with actions that represent what I want to recognize and others with similar actions but do not represent what I want, and all these videos served to train the MLP.
My question: How can I train the MLP network, because all the training I have already done was of time series. In this case I need to gather all the data and inform when the values represent the action and when they do not represent (1 and 0) through a supervised training.
How can I model this data and report that the entire 5000-values group represents the action I want using the R language?
" I want using the R language?" -- sorry, but in this case you're wrong here. opencv is a c++ library (with python & java wrappers)
I used C ++ to collect the data I needed, this part is ready. But I can not think of a way to put the data into a single vector and indicate that they are referring to the action I want to train the neural network.
oh, please show, what you have, so far !
there are several MLP examples on this site. can you try to look at some of those, try out a few things, and refine the question ?
you will need to setup your data into a singe float Mat, with N rows (one per train sample) and M cols(10000 values for 5000 x,y pairs) you also need a N x NumClasses hot-encoded responses Mat.