Polarized Tag Motion Capture in Uncontrolled Lighting
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Solution Overview
Problem
Existing motion capture technologies require controlled lighting conditions and specialized light emission for reflection, which is time-consuming and costly, and are prone to errors due to misidentification of tracking markers by reflective objects.
Innovation Solution
Utilizing polarized light and tags with distinct polarization characteristics to capture motion, allowing motion capture in uncontrolled environments and reducing errors by identifying markers based on polarization characteristics.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If controlled lighting conditions and specialized light emission are used for motion capture, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent replaces the mechanical/optical lighting system with a magnetic field-based detection system. Instead of using specialized light emission and reflection, the system uses magnets attached to markers that are detected by magnetic sensors, eliminating the need for controlled lighting conditions while maintaining measurement precision.
Solution Approach 2:
The patent introduces magnets as an intermediary between the markers and the detection system. The magnets serve as the mediating element that enables detection without requiring direct optical interaction, thereby removing the dependency on controlled lighting conditions and specialized light emission equipment.
2Measurement precision
If controlled lighting conditions are used for motion capture, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent replaces the lighting-based detection system with a magnetic field-based system, which eliminates the need for setup and control of lighting conditions. This substitution directly reduces the time required for motion capture setup while maintaining the ability to accurately identify markers.
3Ease of operation
If reflective objects are used for motion capture, then ease of operation is improved, but reliability decreases
Solution Approach 1:
The patent replaces optical reflection-based detection with magnetic field-based detection. This substitution eliminates the problem of reflective objects interfering with marker identification, as magnetic fields are not affected by the reflective properties of surrounding objects, thereby improving reliability while maintaining ease of operation.
Solution Approach 2:
The patent introduces magnets as an intermediary that provides a reliable detection mechanism independent of optical reflections. The magnets create a distinct magnetic signature that can be reliably detected regardless of the reflective properties of nearby objects, thus improving marker identification accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables motion capture in uncontrolled lighting conditions, reduces computational requirements, and minimizes errors in marker identification, thereby improving accuracy and reducing the need for specialized lighting.
Implementation Method 1
Motion capture using light polarization... utilizing polarized light and tags with distinct polarization characteristics to capture motion
Data Source
AI summary
A system may perform motion capture using polarized light. For example, the system may determine one or more filtered pixels having an associated degree of linear polarization above a threshold from a plurality of pixels of an image captured by a polarization camera and determine a set of pixels of the filtered pixels are associated with a polarized tag, the polarized tag being on a subject of motion capture. The system may then determine an orientation of the polarized tag based on one or more angles of polarization of the pixels associated with the polarized tag and generate a motion capture pose for a model based on a location of the set of pixels of the filtered pixels in the image and the orientation of the polarized tag.


