Roku, Inc. (20240245956). Platform for Visual Tracking of User Fitness simplified abstract
Contents
Platform for Visual Tracking of User Fitness
Organization Name
Inventor(s)
Karina Levitian of Austin TX (US)
Sunil Ramesh of Cupertino CA (US)
Michael Cutter of Golden CO (US)
Preethi Parasseri Narayanan of Cupertino CA (US)
Platform for Visual Tracking of User Fitness - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240245956 titled 'Platform for Visual Tracking of User Fitness
The abstract of this patent application describes a method that involves receiving video of a user performing a fitness exercise, estimating skeletal movement using a detection model, generating a synthetic video based on the estimated movement, comparing it to a reference movement, and displaying the results on a content-presentation device.
- Using video from cameras to track user movement during a fitness exercise
- Estimating skeletal movement using a detection model
- Generating a synthetic video based on the estimated movement
- Comparing estimated movement to a reference movement for the exercise
- Displaying the synthetic video, reference video, and a metric indicating the difference on a content-presentation device
Potential Applications: - Fitness tracking and analysis - Virtual coaching for exercise routines - Rehabilitation monitoring for physical therapy
Problems Solved: - Providing real-time feedback on exercise form - Improving user performance during fitness activities - Enhancing the effectiveness of workout sessions
Benefits: - Accurate tracking of skeletal movement - Personalized feedback for users - Enhanced motivation and engagement during workouts
Commercial Applications: Title: "Real-time Fitness Tracking and Coaching System" This technology can be used in fitness centers, rehabilitation facilities, and home workout systems to offer personalized coaching and performance monitoring for users.
Questions about the technology: 1. How does the system ensure accurate estimation of skeletal movement during various fitness exercises? 2. What are the potential limitations of using synthetic video feedback for improving exercise form?
Original Abstract Submitted
in one aspect, an example method includes (i) receiving, from one or more cameras in a viewing environment of a content-presentation device, video of a user performing a fitness exercise in the viewing environment; (ii) using the received video and a skeletal detection model to estimate skeletal movement of the user; (iii) generating a synthetic video representing the user moving according to the estimated skeletal movement; (iv) based on a comparison of the estimated skeletal movement with predefined reference skeletal movement representing desired skeletal movement for the fitness exercise, and while the user is performing the fitness exercise, continually calculating a metric representing a difference between the estimated skeletal movement and the reference skeletal movement; and (v) causing the content-presentation device to concurrently display the generated synthetic video, a reference video representing the reference skeletal movement, and an indication of the metric.
