TY - JOUR
T1 - Human behavior classification using thinning algorithm and support vector machine
AU - Widyanto, Muhammad Rahmat
AU - Endah, Sukmawati Nur
AU - Hirota, Kaoru
PY - 2010/1
Y1 - 2010/1
N2 - This paper proposes a skeleton-based human behavior classification system using thinning algorithm and Support Vector Machine (SVM). The proposed system consists of two phases, skeletonization phase where main human body part is constructed using thinning algorithm, and classification phase where the skeleton constructed by previous phase is classified into certain human behavior pose using SVM. Experiment using 44 training and 44 testing data of real human poses shows that the system achieves 81.06% accuracy. This system can be further developed for early detection of criminal action.
AB - This paper proposes a skeleton-based human behavior classification system using thinning algorithm and Support Vector Machine (SVM). The proposed system consists of two phases, skeletonization phase where main human body part is constructed using thinning algorithm, and classification phase where the skeleton constructed by previous phase is classified into certain human behavior pose using SVM. Experiment using 44 training and 44 testing data of real human poses shows that the system achieves 81.06% accuracy. This system can be further developed for early detection of criminal action.
KW - Support vector machine
KW - Thinning algorithm
UR - http://www.scopus.com/inward/record.url?scp=77749289378&partnerID=8YFLogxK
U2 - 10.20965/jaciii.2010.p0028
DO - 10.20965/jaciii.2010.p0028
M3 - Article
AN - SCOPUS:77749289378
SN - 1343-0130
VL - 14
SP - 28
EP - 33
JO - Journal of Advanced Computational Intelligence and Intelligent Informatics
JF - Journal of Advanced Computational Intelligence and Intelligent Informatics
IS - 1
ER -
