M
Mark
I'm using AdaBoost on optical flow data to learn to recognize human
actions. I've split my optical flow data into 5 channels (positive x,
negative x, positive y, negative y, and 'zero'). I know how to use
AdaBoost on a single channel, but I'm not sure how to combine the 5
channels to form a better classifier. Do I run AdaBoost on each
channel, and then pass the 5 outputs to another AdaBoost, or should I
simply concatenate the 5 channels and run AdaBoost once on all of
them?
Thanks,
Mark
actions. I've split my optical flow data into 5 channels (positive x,
negative x, positive y, negative y, and 'zero'). I know how to use
AdaBoost on a single channel, but I'm not sure how to combine the 5
channels to form a better classifier. Do I run AdaBoost on each
channel, and then pass the 5 outputs to another AdaBoost, or should I
simply concatenate the 5 channels and run AdaBoost once on all of
them?
Thanks,
Mark