Gesture Classification

I’ve revisited a simple video dataset I created a while back, where I raise either my right or left hand, using my latest image processing algorithms. The initial results are excellent, with 100% accuracy, and what’s better, the preprocessing step where each image frame of the video is converted to a data structure now takes about .2 seconds per frame, allowing for 5 frames per second to be processed. The prediction step, where a sequence of frames (already converted into a data structure) is classified as either a left hand or right hand sequence, takes about .01 seconds per sequence. This suggests as a general matter these algorithms can be applied to real time gesture classification given underlying video. As a result, I’m going to pursue the matter a bit further, and if other gestures can be classified with comparable accuracy, then I’m going to invest the time and write software in a language native to Apple devices, with the goal of substituting a mouse with gestures, but in a way that not only works, but is intuitive and easy to use. Moreover, I suspect there’s enough information in posture alone to figure out where it is that you’re pointing, which could allow users to simply touch the screen, even though their hands aren’t visible. That is, the webcam doesn’t need to see your hand, to know where you’re pointing.

Gesture Dataset

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