Recognition of Yoga poses through an interactive system with Kinect based on confidence value

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%.

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

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

[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]  Choubik Youness,et al.  Machine Learning for Real Time Poses Classification Using Kinect Skeleton Data , 2016, CGiV 2016.

[5]  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).

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

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

[8]  Abdelhak Mahmoudi,et al.  Machine Learning for Real Time Poses Classification Using Kinect Skeleton Data , 2016, 2016 13th International Conference on Computer Graphics, Imaging and Visualization (CGiV).

[9]  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).

[10]  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).

[11]  Sheng-Luen Chung,et al.  Automatic action segmentation and continuous recognition for basic indoor actions based on kinect pose streams , 2017, 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[12]  Peijiang Yuan,et al.  Recognition of Yoga Poses Through an Interactive System with Kinect Device , 2018, 2018 2nd International Conference on Robotics and Automation Sciences (ICRAS).

[13]  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).