To: galt%peruvian@cs.utah.edu
Subject: Re: simple code to get simple gestures
Cc: glove-list@karazm.math.uh.edu
Message-Id: <9110141111.AA08568@roi.ca41.csd.mot.com>
Date: 14 Oct 91 11:11:36 PDT (Mon)
From: Lance Norskog <lance@roi.ca41.csd.mot.com>

Yes, Fred Brooks of the Pixel-Planes project said that predictive
tracking should work best.  

Graphics Gems II has a thing on predictive coding as compression technique.
Here's the idea: you have a state machine which reads a sample stream and 
guesses the next sample, and output the difference between your guess
and the actual sample.  This should give you lots of samples with low
values, suitable for Huffman or dictionary compression.  I've been
itching to try this on sound samples.  The article does it on pictures,
and shows the error output as a separate picture.  It's an excellent
demonstration of the principle.

A first attempt would track the slope of the last few samples, thus
extending the first derivative out.  If you assume that the input
stream is delayed by X milliseconds, and it samples at half your
update rate, you can create a separate one-dimensional tracker
for each of (X, Y, Z, rot) and do a better job than drawing
from raw input.  You can also reject weird inputs, and average
noisy ones.

If you move your hand fast and then stop, the predictive tracking
will overshoot and come back to the resting place.  Cest la vie.

I'd say it's time to sample movements, run the output through
a statistics package, and figure out just what kind of error
you need to deal with.

Lance Norskog