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Classifying complex human motion using point distribution models

conference contribution
posted on 2002-01-01, 00:00 authored by E Tassone, G West, Svetha VenkateshSvetha Venkatesh
The Point Distribution Model (PDM) has been successfully used in modelling shape variations in groups of static images. It has also been effectively adapted to temporal image sets and used to track moving bodies such as hands and walking persons. However standard models do not consider the temporal characteristics of the data and are purely models of shape. This research proposes an extension to the PDM which explicitly considers the temporal sequencing of the images in the motion. The modified model can then be built from temporal quantities such as linear velocity and acceleration which are derived from the images. The new model formulation also enables movements to be tracked and classified according to their distinguishing temporal characteristics. This has been tested against distinct sets of arm movements under varying sets of experimental conditions.

History

Event

Asian Conference on Computer Vision (5th : 2002 : Melbourne, Vic.)

Pagination

138 - 143

Publisher

Asian Federation of Computer Vision Societies

Location

Melbourne, Vic.

Place of publication

[Tokyo, Japan]

Start date

2002-01-23

End date

2002-01-25

ISBN-13

9780958025607

ISBN-10

0958025606

Language

eng

Publication classification

E1.1 Full written paper - refereed

Editor/Contributor(s)

D Suter, A Bab-Hadiashar

Title of proceedings

ACCV 2002 : Proceedings of the 5th Asian Conference on Computer Vision

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