Problem: Given a six-sided die, fitted with accelerometers, we want to estimate which side is up by just looking at the accelerometer data.
Solution: We model each side by a multivariate Gaussian, and perform Maximum Likelihood (ML) estimation.
Concrete: Within the die, two dual-axis accelerometers are fitted, so we'll have 4 values, two of which should behave approximately the same. See the cubicles website for more information. The input vectors, Gaussians, and mean vectors are therefore four-dimensional.
[1: Gaussian Modelling] [2: Maximum Likelihood Estimation] [3: generating the PICC-code] [4: visualization] [5: adding gestures]
For a background on Bayesian Learning, we refer to [Tom Mitchell, Machine Learning].
We start with Bayes theorem:
Document created by Kristof Van Laerhoven, March 2003.