Markerless Body Joint Tracking via 3D Cylindrical Models
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Solution Overview
Problem
Conventional real-time body joint tracking methods face challenges due to occlusion, ambiguity, lighting conditions, and dynamic objects, particularly in marker-based systems that require obtrusive devices and are costly, making them unsuitable for prolonged rehabilitation therapy.
Innovation Solution
A method and system that utilize 3D cylindrical models initialized from 3D point cloud data to track body joints, employing a particle filter mechanism to obtain optimized motion trajectories based on direction angles and base coordinates, reducing noise from depth sensors and improving tracking accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If marker-based joint tracking methods are used, then tracking accuracy is improved, but device complexity and cost increase significantly
Solution Approach 1:
The patent extracts and removes the markers from the tracking system, transitioning from marker-based to markerless joint tracking. This eliminates the need for obtrusive devices while maintaining tracking functionality through direct analysis of body geometry from depth images.
Solution Approach 2:
The patent creates a virtual 3D model (cylindrical representation) that copies and represents the actual body segments. This virtual model allows tracking without physical markers, replicating the essential geometric properties needed for accurate joint position estimation.
2Measurement precision
If marker-based joint tracking methods are used, then tracking accuracy is improved, but ease of operation deteriorates due to obtrusive devices
Solution Approach 1:
The patent removes markers completely from the system, eliminating devices that subjects must wear. This extraction of unnecessary components directly improves ease of operation and user comfort while maintaining tracking capability through alternative methods.
3Ease of operation
If conventional markerless joint tracking is used, then ease of operation is improved, but measurement precision deteriorates due to occlusion and ambiguity
Solution Approach 1:
The patent segments the body into distinct cylindrical regions corresponding to different body parts (arms, legs, torso). This segmentation allows independent tracking of each segment, reducing ambiguity and improving precision even when parts of the body are occluded, as each segment can be tracked separately using its geometric properties.
Solution Approach 2:
The patent changes the representation parameters from direct 2D image coordinates to 3D cylindrical model parameters (position, orientation, scale). This parameter transformation enables more robust tracking by incorporating depth information and geometric constraints, improving precision under varying lighting and occlusion conditions.
4Ease of operation
If conventional markerless joint tracking is used, then ease of operation is improved, but reliability deteriorates in challenging lighting and occlusion conditions
Solution Approach 1:
The patent transitions from 2D image plane tracking to 3D space tracking using depth information and cylindrical models. By adding the depth dimension and using 3D geometric constraints, the system achieves more reliable tracking that is less sensitive to variations in lighting conditions and occlusions that primarily affect 2D image analysis.
Data Source
AI summary
Body joint tracking is applied in various industries and medical field. In body joint tracking, marker less devices plays an important role. However, the marker less devices are facing some challenges in providing optimal tracking due to occlusion, ambiguity, lighting conditions, dynamic objects etc. System and method of the present disclosure provides an optimized body joint tracking. Here, motion data pertaining to a first set of motion frames from a motion sensor are received. Further, the motion data are processed to obtain a plurality of 3 dimensional cylindrical models. Here, every cylindrical model among the plurality of 3 dimensional cylindrical model represents a body segment. The coefficients associated with the plurality of 3 dimensional cylindrical models are initialized to obtain a set of initialized cylindrical models. A set of dynamic coefficients associated with the initialized cylindrical models are utilized to track joint motion trajectories of a set of subsequent frames.