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Classifying complex human motion using point distribution models

Tassone, Ezra, West, Geoff and Venkatesh, Svetha 2002, Classifying complex human motion using point distribution models, in ACCV 2002 : Proceedings of the 5th Asian Conference on Computer Vision, Asian Federation of Computer Vision Societies, [Tokyo, Japan], pp. 138-143.

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Title Classifying complex human motion using point distribution models
Author(s) Tassone, Ezra
West, Geoff
Venkatesh, Svetha
Conference name Asian Conference on Computer Vision (5th : 2002 : Melbourne, Vic.)
Conference location Melbourne, Vic.
Conference dates 23-25 Jan. 2002
Title of proceedings ACCV 2002 : Proceedings of the 5th Asian Conference on Computer Vision
Editor(s) Suter, D.
Bab-Hadiashar, A.
Publication date 2002
Conference series Asian Conference on Computer Vision
Start page 138
End page 143
Total pages 6
Publisher Asian Federation of Computer Vision Societies
Place of publication [Tokyo, Japan]
Keyword(s) point distribution model (PDM)
static images
data
temporal sequencing
Summary 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.
ISBN 0958025606
9780958025607
Language eng
Field of Research 089999 Information and Computing Sciences not elsewhere classified
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1.1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044892

Document type: Conference Paper
Collection: School of Information Technology
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