Monday, July 22, 2013

We identify objects after compensating for variability

Writing a paper about best model estimation and finally came to a very simple initial statement:

"Geometric invariants are considered important in mathematics as the quantities that identify geometric objects [Weyl]. They are also important in shape recognition and robotics where an object is to be identified or recognized independently of its position, distance, or angle of presentation to the viewer – which is to say independently of its variants. This paper assumes we can measure an object’s variants and expresses the simple idea that recognition is a composition of a variant factor with an invariant one. In terms of measuring the variants, it states the obvious: we identify what is left after taking out the variability. "


  1. When you are observing something empirically, the hard part is figuring out what is irrelevant and what is not. I always thought the way that happens is by comparing many examples.

  2. ...but that probably misses something essential in how our natural makeup evolved.