3-D Human Pose Estimation by Convolutional Neural Network in The Video Traditional Martial Arts Presentation

Authors: Nguyen Tuong Thanh*, Lê Văn Hùng, Phạm Thành Công


Preservation and maintenance of traditional martial arts and teaching martial arts are very important activities in social life. It helps preserve national culture, train health, and self-defense for people. However, traditional martial arts have many different postures and activities of the body and body parts. In this paper, we are proposed using deep learning with Convolutional Neural Network (CNN) for estimating key points and joints of actions in traditional martial art postures and proposed the evaluation methods. The training set has been learned on the 2016 MSCOCO Key points Challenge classic database [21], the results are evaluated on 14 videos of traditional martial art performances with complicated postures. The estimated results are high and published. In particular, we are presented the results of estimating key points and joints in 3-D space to support the construction of a traditional martial arts conservation and teaching application.


Estimation of key points, Deep learning, Skeleton,Dancing and teaching of traditional martial arts
Pages : 43-49

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