Recognizing Animals Using Motion Parts

Kong Changming, A Calway, M Mirmehdi

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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 contributionRecognizing Animals Using Motion Parts
Original languageEnglish
Title of host publicationUnknown
PublisherBMVA Press
Pages796 - 808
Number of pages12
ISBN (Print)1901725294
Publication statusPublished - Sept 2005

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the 16th British Machine Vision Conference

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