Abstract
Human action recognition is an important research topic that has many potential applications such as video surveillance, human-computer 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.
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Acknowledgments
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]
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Kwon, B. et al. (2015). Implementation of Human Action Recognition System Using Multiple Kinect Sensors. In: Ho, YS., Sang, J., Ro, Y., Kim, J., Wu, F. (eds) Advances in Multimedia Information Processing -- PCM 2015. PCM 2015. Lecture Notes in Computer Science(), vol 9314. Springer, Cham. https://doi.org/10.1007/978-3-319-24075-6_32
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DOI: https://doi.org/10.1007/978-3-319-24075-6_32
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