Identifying semi-Invariant Features on Mouse Contours

P.A. Crook, T.C. Lukins, J. Heward, J.D. Armstrong
2008 Procedings of the British Machine Vision Conference 2008  
This paper addresses the problem of reliably fitting an orientated model to video data of laboratory mice assays by specifically locating semi-invariant points on an extracted outline. In the case of mice, the rapid changes in direction and shape often lead to failure when using explicit models. Here we employ a standard background subtraction algorithm in order to derive contour information from a well defined top-down view of the assay. Using this contour, we compare three different
more » ... different approaches at locating head, tail-tip and tail-base features that allow us to constrain orientation. We validate each approach against an annotated gold-standard data-set, and conclude that a composite method delivers the best results. This ultimately has benefits for analysing higher-level behaviour where it is crucial to retain orientation.
doi:10.5244/c.22.84 dblp:conf/bmvc/CrookLHA08 fatcat:r2el6v5sajcnfh7p3y32qwxtou