Hi all, I'm new to computer vision/machine learning and I was hoping I could ask the community for some advise. I've calculated HoG descriptors for frames in a video but I'm not sure how best to group/join/??? them so I can then run Kmeans clustering on them. I'm hoping to use the (Visual) Bag of Words method to classify using random forrests but I'm a novice when it comes to ndarrays and not sure of the correct terminology.
I know the HoG descriptors are flattened arrays but in order to cluster the frames/image descriptors I would need to group all the descriptors together. What is the best way to create a data structure suitable for kmeans when you have 100,000's of individual descriptors and do I need to pre-process the ndarrays ? Michael -- You received this message because you are subscribed to the Google Groups "scikit-image" group. To unsubscribe from this group and stop receiving emails from it, send an email to scikit-image+unsubscr...@googlegroups.com. To post to this group, send an email to scikit-image@googlegroups.com. To view this discussion on the web, visit https://groups.google.com/d/msgid/scikit-image/e1b83557-9418-475e-a5c3-33d7d4ff7a20%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
