A framework for correcting human motion alignment for traditional dance training using augmented reality

• Main Authors: Iqbal, Javid, Sidhu, Manjit Singh
• Format: Conference or Workshop Item
• Language: English
• Published: 2016
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://repo.uum.edu.my/20029/1/KMICe2016%2059%2063.pdf; http://repo.uum.edu.my/20029/; http://www.kmice.cms.net.my/kmice2016/files/KMICe2016_eproceeding.pdf
• Institution: Universiti Utara Malaysia

This paper presents a framework for motion capture analysis for dance learning technology using Microsoft Kinect V2. The proposed technology utilizes motion detection, emotion analysis, coordination analysis and interactive feedback techniques for a particular dance style selected by the trainee.This motion capture system solves the heterogeneity of the existing dance learning system and hence provides robustness. The analysis of the proposed work is carried out using query techniques and heuristic evaluation. The Microsoft Kinect V2 embedded with Augmented Reality (AR) technology is explored to demonstrate the recognition accuracy of the proposed framework.