1-2hit |
Naoya OHTA Kenichi KANATANI Kazuhiro KIMURA
We show that moving objects can be detected from optical flow without using any knowledge about the magnitude of the noise in the flow or any thresholds to be adjusted empirically. The underlying principle is viewing a particular interpretation about the flow as a geometric model and comparing the relative "goodness" of candidate models measured by the geometric AIC.
Iman TRIONO Naoya OHTA Kenichi KANATANI
We implement a graphical interface that automatically transforms a figure input by a mouse into a regular figure which the system infers is the closest to the input. The difficulty lies in the fact that the classes into which the input is to be classified have inclusion relations, which prohibit us from using a simple distance criterion. In this letter, we show that this problem can be resolved by introducing the geometric AIC.