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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 VenkateshThe 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 - 143Publisher
Asian Federation of Computer Vision SocietiesLocation
Melbourne, Vic.Place of publication
[Tokyo, Japan]Start date
2002-01-23End date
2002-01-25ISBN-13
9780958025607ISBN-10
0958025606Language
engPublication classification
E1.1 Full written paper - refereedEditor/Contributor(s)
D Suter, A Bab-HadiasharTitle of proceedings
ACCV 2002 : Proceedings of the 5th Asian Conference on Computer VisionUsage metrics
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