Artificial Intelligence has been helping in various aspects of human life. The technology has touched almost every industry; be it medical application, mobility, healthcare, or retail. And, now AI has made its way to the fitness industry. Generally, when it comes to fitness, a lot of people think about diet, cardio, gym, and the most popular option of all, yoga. Yoga has been the most favored one because it doesn't only benefit young adults, but also people who are old. Here pose estimation is going to take action.
This app demonstrates a Yoga assistant mobile application based on human-key points detection models, which imitates the scene that real Yoga tutors guide and supervise their students to do Yoga via the video. In order to provide humanize, safe and convenient service, the core function is designed good interface, and embedding fast and accurate models to detect key points and calculate the scores. In addition, we propose an improved to calculate scores that can be applied to all poses. Our application is evaluated on different Yoga poses under different scenes, and its robustness is guaranteed. Exercises and sports technological assistances are implemented in yoga pose identification. In this work, a self-assistance-based yoga posture identification technique is developed, which helps users to perform Yoga with the correction feature in Real-time.
Keywords: Yoga tutors, Yoga poses, pose identification.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.
System Requirements
Processor - I3/Intel Processor.
· RAM - 8GB (min).
· Hard Disk - 1 TB.
S/W CONFIGURATION:
• Operating System : Windows 7+.
• Programming : Java
• Server-side Script : PHP
• IDE : Android Studio.
• SDK : Android
• Libraries Used : Volley, Material design.