• Journal of Internet Computing and Services
    ISSN 2287 - 1136 (Online) / ISSN 1598 - 0170 (Print)
    https://jics.or.kr/

Silhouette-based motion recognition for young children using an RBF network


Hye-Jeong Kim, Kyoung-Mi Lee, Journal of Internet Computing and Services, Vol. 8, No. 3, pp. 119-130, Jun. 2007
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Keywords: motion recognition, RBF network, movement education for young children

Abstract

To recognition a human motion, in this paper, we propose a neural approach using silhouettes in video frames captured by two cameras placed at the front and side of the human body. To extract features of the silhouettes for motion estimation, the proposed system computes both global and local features and then groups these features into static and dynamic features depending on whether features are in a static frame. Extracted features are in a static frame. Extracted features are used to train a RBF network. The neural system uses static features as the input of the neural network and dynamic features as additional features for recognition. In this paper, the proposed method was applied to movement education for young children. The basic movements for such education consist of locomotor movements, such as walking, jumping, and hopping, and non-locomotor movements, including bending, stretching, balancing and turning. The system demonstrated the effectiveness of motion recognition for movement education generated by the proposed neural network. The proposed system dan be extended to the system for movement education which develops the spatial sense of young children.


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Cite this article
[APA Style]
Kim, H. & Lee, K. (2007). Silhouette-based motion recognition for young children using an RBF network. Journal of Internet Computing and Services, 8(3), 119-130.

[IEEE Style]
H. Kim and K. Lee, "Silhouette-based motion recognition for young children using an RBF network," Journal of Internet Computing and Services, vol. 8, no. 3, pp. 119-130, 2007.

[ACM Style]
Hye-Jeong Kim and Kyoung-Mi Lee. 2007. Silhouette-based motion recognition for young children using an RBF network. Journal of Internet Computing and Services, 8, 3, (2007), 119-130.