Open AccessShock Graph for Representation and Modeling of Posture
Author(s) -
Tahir Nooritawati Md,
Hussain Aini,
Samad Salina Abdul,
Husain Hafizah
Publication year - 2007
Publication title -
etri journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.295
H-Index - 46
eISSN - 2233-7326
pISSN - 1225-6463
DOI - 10.4218/etrij.07.0106.0110
Subject(s) - representation (politics) , artificial intelligence , computer science , graph , abstraction , feature (linguistics) , pattern recognition (psychology) , feature vector , theoretical computer science , philosophy , linguistics , epistemology , politics , political science , law
Skeleton transform of which the medial axis transform is the most popular has been proposed as a useful shape abstraction tool for the representation and modeling of human posture. This paper explains this proposition with a description of the areas in which skeletons could serve to enable the representation of shapes. We present algorithms for two‐dimensional posture modeling using the developed simplified shock graph (SSG). The efficacy of SSG extracted feature vectors as shape descriptors are also evaluated using three different classifiers, namely, decision tree, multilayer perceptron, and support vector machine. The paper concludes with a discussion of the issues involved in using shock graphs to model and classify human postures.