@inproceedings{ff4b9f3abebb4e838a88529066eb558a,
title = "Recognition of Yoga poses through an interactive system with Kinect based on confidence value",
abstract = "Nowadays, the recognition of poses is a field of investigation that takes incredible significance for oneself preparing in different sports. Kinect offers a low-cost solution for the recognition of Yoga poses due to body tracking and depth sensor. In this research, we propose an interactive system for perceiving a few postures for learning Yoga that will be characterized by a level of trouble and coordinated with command voices to envision the guidelines and pictures about the stances to be execution. Likewise, posture correction instructions will be displayed for the user in real time made by an expert yoga trainer. Besides, the recognition algorithm is based on Adaboost algorithm in order to get a robust database for detecting 6 Asana Yoga poses. All data were obtained and analyzed according to the confidence which showed a maximum average value of 92\%.",
keywords = "Gesture recognition, human computer interaction, kinect, machine learning, sports training, yoga",
author = "Trejo, \{Edwin W.\} and Peijiang Yuan",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 3rd IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2018 ; Conference date: 18-07-2018 Through 20-07-2018",
year = "2019",
month = jan,
day = "11",
doi = "10.1109/ICARM.2018.8610726",
language = "英语",
series = "ICARM 2018 - 2018 3rd International Conference on Advanced Robotics and Mechatronics",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "606--611",
booktitle = "ICARM 2018 - 2018 3rd International Conference on Advanced Robotics and Mechatronics",
address = "美国",
}