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Threshold dynamic time warping for spatial activity recognition

Riedel, Daniel Erwin, Venkatesh, Svetha and Liu, Wanquan 2007, Threshold dynamic time warping for spatial activity recognition, International journal of information and systems sciences, vol. 3, no. 3, pp. 392-405.

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Title Threshold dynamic time warping for spatial activity recognition
Author(s) Riedel, Daniel Erwin
Venkatesh, Svetha
Liu, Wanquan
Journal name International journal of information and systems sciences
Volume number 3
Issue number 3
Start page 392
End page 405
Total pages 14
Publisher Institute for Scientific Computing and Information
Place of publication Alberta, Canada
Publication date 2007
ISSN 1708-296X
Keyword(s) namic time warping
hidden markov model
spatial activity
recognition
sequence alignment
Summary Non-invasive spatial activity recognition is a difficult task, complicated by variation in how the same activities are conducted and furthermore by noise introduced by video tracking procedures. In this paper we propose an algorithm based on dynamic time warping (DTW) as a viable method with which to quantify segmented spatial activity sequences from a video tracking system. DTW is a widely used technique for optimally aligning or warping temporal sequences through minimisation of the distance between their components. The proposed algorithm threshold DTW (TDTW) is capable of accurate spatial sequence distance quantification and is shown using a three class spatial data set to be more robust and accurate than DTW and the discrete hidden markov model (HMM). We also evaluate the application of a band dynamic programming (DP) constraint to TDTW in order to reduce extraneous warping between sequences and to reduce the computation complexity of the approach. Results show that application of a band DP constraint to TDTW improves runtime performance significantly, whilst still maintaining a high precision and recall.
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 890205 Information Processing Services (incl. Data Entry and Capture)
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2007, Institute for Scientific Computing and Information
Persistent URL http://hdl.handle.net/10536/DRO/DU:30044281

Document type: Journal Article
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.