Center of Mass State Vector for 3D Motion Analysis
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Solution Overview
Problem
Conventional tracking systems face challenges in accurately analyzing and providing feedback on user motion, particularly for exercises that require precise understanding and subtle differences in motion, such as squats and push-ups, as they struggle to recognize subtle variations in body position and weight distribution.
Innovation Solution
The system determines a center of mass state vector based on a body model formed from depth images, including center-of-mass position, velocity, acceleration, orientation, angular velocity, and inertia tensor, to analyze user motion and provide feedback on exercise form, using geometric shapes and skeletal tracking data to compute these parameters and apply constraint forces.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional tracking systems are used to analyze user motion, then the system is simple to operate, but the measurement precision of subtle motion variations is insufficient
Solution Approach 1:
The patent segments the user's body into multiple body parts (head, torso, limbs) and tracks each segment separately using depth images. This segmentation allows for precise measurement of subtle motion variations in different body parts while maintaining a manageable system structure through modular processing of each segment's depth data.
Solution Approach 2:
The patent transitions from 2D image tracking to 3D depth image analysis, adding a dimensional aspect that enables precise measurement of motion in three-dimensional space. This dimensional enhancement allows the system to accurately capture subtle variations in body position, orientation, and movement trajectories without requiring overly complex processing.
2Measurement precision
If detailed body model analysis is performed to accurately detect subtle motion differences, then measurement precision improves, but computation time increases
Solution Approach 1:
The patent replaces complex mechanical tracking systems with optical depth sensing technology. Depth cameras capture three-dimensional body position data directly through light reflection measurements, eliminating the need for multiple sensors, markers, or complex mechanical tracking apparatus. This substitution achieves high measurement precision while reducing computational overhead compared to traditional mechanical or multi-sensor systems.
3Loss of information
If the system tracks only basic joint positions, then processing speed is fast, but the ability to analyze weight distribution and center of mass is insufficient
Solution Approach 1:
The patent creates a universal body model framework that can simultaneously perform multiple functions: tracking joint positions, calculating center of mass, analyzing weight distribution, and detecting subtle motion variations. This multi-functional approach uses the same depth image data and body model structure to derive various motion parameters, ensuring complete motion analysis without requiring separate processing systems for each function.
Data Source
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AI summary
Techniques described herein determine a center of mass state vector based on a body model. The body model may be formed by analyzing a depth image of a user who is performing some motion. The center of mass state vector may include, for example, center-of-mass position, center-of-mass velocity, center-of-mass acceleration, orientation, angular velocity, angular acceleration, inertia tensor, and angular momentum. A center of mass state vector may be determined for an individual body part or for the body as a whole. The center of mass state vector(s) may be used to analyze the user's motion.