Recognition of Yoga Poses Through an Interactive System with Kinect Device

In daily life, Yoga has become a well-known discipline around the world that keep people in good physical and mental health. As well, gesture recognition is a field of investigation that takes great importance for the self-training of various sports using acquisition techniques such as Kinect device. This research proposes an interactive system capable of recognizing 6 poses for learning Yoga that can track up to 6 people at the same time. It is also integrated with command voices to visualize the instructions and pictures about the poses to be performance for the user. In order to get a strong database for recognition, the system used Adaboost algorithm though the software development kit specially for Kinect. All data was trained by an expert yoga trainer and final database showed above 94.78% as maximum value for poses analyzed in terms of accuracy.

[1]  Takeshi Saitoh,et al.  Kinect sensor based sign language word recognition by mutli-stream HMM , 2017, 2017 56th Annual Conference of the Society of Instrument and Control Engineers of Japan (SICE).

[2]  Julie A. Kientz,et al.  Eyes-free yoga: an exergame using depth cameras for blind & low vision exercise , 2013, ASSETS.

[3]  Antonio Gentile,et al.  Real-Time Hand Pose Recognition Based on a Neural Network Using Microsoft Kinect , 2013, 2013 Eighth International Conference on Broadband and Wireless Computing, Communication and Applications.

[4]  Alina Delia Calin,et al.  Variation of pose and gesture recognition accuracy using two kinect versions , 2016, 2016 International Symposium on INnovations in Intelligent SysTems and Applications (INISTA).

[5]  Yuan Yao,et al.  Virtual Personal Trainer via the Kinect Sensor , 2015, 2015 IEEE 16th International Conference on Communication Technology (ICCT).

[6]  Chien-Li Chou,et al.  Computer-assisted self-training system for sports exercise using kinects , 2013, 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW).

[7]  Hubert P. H. Shum,et al.  Kinect Posture Reconstruction Based on a Local Mixture of Gaussian Process Models , 2016, IEEE Transactions on Visualization and Computer Graphics.

[8]  Ajmal S. Mian,et al.  Using Kinect for face recognition under varying poses, expressions, illumination and disguise , 2013, 2013 IEEE Workshop on Applications of Computer Vision (WACV).

[9]  Quang Vinh Nguyen,et al.  A Close-Range Gesture Interaction with Kinect , 2015, 2015 Big Data Visual Analytics (BDVA).

[10]  Hélène Corriveau,et al.  Balance Rehabilitation using Xbox Kinect among an Elderly Population:A Pilot Study , 2015 .

[11]  Aciek Ida Wuryandari,et al.  Inverse kinematics and gesture pattern recognition using Hidden Markov Model on BeatMe! project: Traditional dance digitalization , 2015, 2015 International Conference on Electrical Engineering and Informatics (ICEEI).

[12]  S. J. Hwang,et al.  Ada-Boostbased Gesture Recognition using Time Interval Window , 2015 .