2D Motion Tracking With Virtual Space Mapping for Exercise
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Solution Overview
Problem
Existing motion tracking systems for physical rehabilitation and exercise require expensive 3D sensors, which are difficult to install and use, while 2D cameras are widely available but pose challenges in accurately tracking user movements.
Innovation Solution
A method and system using a 2D camera with a processor to detect points on a subject's body, calculate a reference ratio, map these points into virtual space, and output movements on a display, utilizing machine learning for detection and correction, ensuring accurate 2D motion tracking without the need for specialized 3D sensors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If 3D motion tracking systems are used, then motion tracking accuracy is improved, but device cost and complexity increase
Solution Approach 1:
The patent creates a virtual 3D representation of the user by mapping 2D camera images to a 3D virtual space. Instead of using complex 3D sensors, the system copies the user's appearance and movements into a simplified virtual environment, achieving 3D-like tracking accuracy through computational geometry rather than hardware complexity
Solution Approach 2:
The system transitions from 2D camera images to 3D virtual space representation by calculating depth information and perspective transformations. This dimensional transformation allows the system to maintain 3D motion tracking accuracy while using simple 2D cameras, resolving the contradiction between precision and complexity
2Measurement precision
If 3D sensors are used, then motion tracking accuracy is improved, but ease of installation and use deteriorates
Solution Approach 1:
The patent replaces complex 3D sensors with a virtual copying mechanism that uses standard 2D cameras to create digital representations of the user. This virtual copy approach eliminates the need for specialized hardware installation while maintaining tracking accuracy through computational methods
Solution Approach 2:
The system substitutes mechanical 3D sensing hardware with a computational geometry-based virtual modeling system. By replacing physical sensors with algorithmic processing of 2D images, the patent achieves the same tracking functionality with much simpler installation and operation requirements
3Device complexity
If 2D cameras are used, then device cost is reduced, but motion tracking accuracy deteriorates
Solution Approach 1:
The patent overcomes the inherent 2D limitation by implementing perspective transformation and depth calculation algorithms that convert 2D camera data into 3D spatial understanding. This dimensional enhancement allows standard 2D cameras to achieve accuracy previously requiring expensive 3D sensors
Solution Approach 2:
The system introduces virtual space as an intermediary between the 2D camera and the physical world. By mapping 2D images to a virtual 3D representation, the system bridges the accuracy gap between simple cameras and complex sensors through computational geometry and perspective correction
Data Source
AI summary
There is provided a method and system for 2D motion tracking of a subject engaging in physical exercise using a 2D camera. An image including a portion of a body of the subject is received and a first and a second point on the body are detected. A reference distance between the first and second point is determined, and a reference ratio is calculated based on the reference distance and at least one of the height and the width of the image. The first and second point are mapped into virtual space based on the reference ratio to obtain a first and second virtual point. A movement of at least one of the first and second point is detected in another image and mapped to a movement of a corresponding one of the first and second virtual point in virtual space which is output on a display interface.