Real Time Object Oriented 6-Point Skeleton Extraction Component from Human Silhouette for Video Surveillance and Analysis Application

  • Mohamad Hanif Md SaadEmail author
  • Muhammad Faiz Mohd Shukri
  • Win Kong
  • Wan Noor Aziezan Baharuddin
  • Aini Hussain
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9429)


This paper describes the design and implementation of a fast 6-Point skeleton extraction algorithm from human silhouette images which can be used for real-time video surveillance and analysis applications. The 6 Points of Interest (POIs) are sacroiliac support point (P c ), head (P h ), right and left shoulders (P sr and P sl ) and right and left foot (P fr and P fl ). The algorithm was implemented as an object class library and can be used in Microsoft.NET development environment across multiple.NET compatible programming language such as C#, VB.Net and IronRuby. The developed class library successfully tracked the POIs across live video frames in real-time. The applicability of the developed class library for video surveillance and analysis application was proven via its application in the development of the Intelligent Video Surveillance System (InViSSTM). A simple, general purpose case study, which shows the use of the developed.NET components for simple gait analysis application is also discussed in the end of this paper to prove that it is general enough to be used for video surveillance and analysis related applications.


6-Point skeleton Human silhouette analysis Object oriented programming 



The authors would like to express their gratitude to the Government of Malaysia and Universiti Kebangsaan Malaysia for financing this research via the GUP-2013-035 Research Grant.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Mohamad Hanif Md Saad
    • 1
    Email author
  • Muhammad Faiz Mohd Shukri
    • 1
  • Win Kong
    • 1
  • Wan Noor Aziezan Baharuddin
    • 1
  • Aini Hussain
    • 1
  1. 1.Smart Engineering System Research Group, Faculty of Engineering and Built EnvironmentUniveristi Kebangsaan MalaysiaBandar Baru BangiMalaysia

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