Identifying semi-Invariant Features on Mouse Contours

P.A. Crook, T.C. Lukins, J. Heward, J. D. Armstrong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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 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.
Original languageEnglish
Title of host publicationProceedings of the British Machine Vision Conference
PublisherBMVA Press
Number of pages10
Publication statusPublished - 2008


Dive into the research topics of 'Identifying semi-Invariant Features on Mouse Contours'. Together they form a unique fingerprint.

Cite this