loading...
Automatic Classification of Hand Drawn Geometric Shapes using Constructional Sequence Analysis
Edinburgh, Scotland August 03-August 06
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227808Seventh International Conference on D ...
 This Article 
 
Buy PURCHASE ARTICLE: $19
PDF
HTML
Buy IEEE Xplore Subscribers
 
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
ASCII Text
x 
 
R.M. Guest, S. Chindaro, M.C. Fairhurst, J.M. Potter, "Automatic Classification of Hand Drawn Geometric Shapes using Constructional Sequence Analysis," Document Analysis and Recognition, International Conference on, vol. 2, pp. 990, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2, 2003.
 
 
BibTex
x
 
@article{ 10.1109/ICDAR.2003.1227808,
author = {R.M. Guest and S. Chindaro and M.C. Fairhurst and J.M. Potter},
title = {Automatic Classification of Hand Drawn Geometric Shapes using Constructional Sequence Analysis},
journal ={Document Analysis and Recognition, International Conference on},
volume = {2},
year = {2003},
isbn = {0-7695-1960-1},
pages = {990},
doi = {http://doi.ieeecomputersociety.org/10.1109/ICDAR.2003.1227808},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Document Analysis and Recognition, International Conference on
TI - Automatic Classification of Hand Drawn Geometric Shapes using Constructional Sequence Analysis
SN - 0-7695-1960-1
SP
EP
A1 - R.M. Guest,
A1 - S. Chindaro,
A1 - M.C. Fairhurst,
A1 - J.M. Potter,
PY - 2003
KW - null
VL - 2
JA - Document Analysis and Recognition, International Conference on
ER -
 
R.M. Guest, University of Kent
S. Chindaro, University of Kent
M.C. Fairhurst, University of Kent
J.M. Potter, Kent and Canterbury Hospital
A method for automatically assessing the constructional sequence from a neuropsychological drawing task using Hidden Markov Models is presented. We also present a method of extracting and identifying the position of individual pen strokes relating to individual sides of a shape within a drawing to form training and testing sequences. Our results from two experiments using data from patients with visuo-spatial neglect show the HMM classifier is able to generalise on incorrectly extracted sequences and obtain a diagnostic classification which can be used alongside other forms of conventional assessment.
Citation:
R.M. Guest, S. Chindaro, M.C. Fairhurst, J.M. Potter, "Automatic Classification of Hand Drawn Geometric Shapes using Constructional Sequence Analysis," icdar, vol. 2, pp.990, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 2, 2003
Usage of this product signifies your acceptance of the Terms of Use.