Implementation of human action recognition system using multiple kinect sensors

Beom Kwon, Doyoung Kim, Junghwan Kim, Inwoong Lee, Jongyoo Kim, Heeseok Oh, Haksub Kim, Sanghoon Lee

Research output: Contribution to journalConference articlepeer-review

13 Citations (Scopus)


Human action recognition is an important research topic that has many potential applications such as video surveillance, humancomputer interaction and virtual reality combat training. However, many researches of human action recognition have been performed in single camera system, and has low performance due to vulnerability to partial occlusion. In this paper, we propose a human action recognition system using multiple Kinect sensors to overcome the limitation of conventional single camera based human action recognition system. To test feasibility of the proposed system, we use the snapshot and temporal features which are extracted from three-dimensional (3D) skeleton data sequences, and apply the support vector machine (SVM) for classification of human action. The experiment results demonstrate the feasibility of the proposed system.

Original languageEnglish
Pages (from-to)334-343
Number of pages10
JournalLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publication statusPublished - 2015
Event16th Pacific-Rim Conference on Multimedia, PCM 2015 - Gwangju, Korea, Republic of
Duration: 2015 Sept 162015 Sept 18

Bibliographical note

Funding Information:
This work was supported by the ICT R&D program of MSIP/IITP. [R0101-15-0168, Development of ODM-interactive Software Technology supporting Live-Virtual Soldier Exercises]

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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