Abstract
We describe a method for automatically recognizing animals in image sequences
based on their distinctive locomotive movement patterns. The 2-D
motion field associated with the animal is represented using a ""configuration
of motion parts"" model, the characteristics of which are learned from training
data. We adopt an unsupervised approach to learning model parameters,
based on minimal a priori knowledge of the physical or locomotive characteristics
of the animals concerned. Results are presented demonstrating
excellent classification performance, with accuracy exceeding 98% on a test
set consisting of over 100 sequences of 7 different species.
| Translated title of the contribution | Recognizing Animals Using Motion Parts |
|---|---|
| Original language | English |
| Title of host publication | Unknown |
| Publisher | BMVA Press |
| Pages | 796 - 808 |
| Number of pages | 12 |
| ISBN (Print) | 1901725294 |
| Publication status | Published - Sep 2005 |