An algorithm to correct for camera vibrations in optical motion tracking systems

Area of Science:

• Biomechanics
• Computer Vision
• Robotics

Background:

• Marker-based infrared motion tracking typically requires static camera setups.
• Camera movement introduces significant errors in 3D motion reconstruction.
• Existing methods are limited in handling dynamic or accelerated camera systems.

Purpose of the Study:

• To develop and validate a correction algorithm for 3D motion capture data affected by camera vibrations.
• To enable accurate motion reconstruction in setups with moving or accelerated cameras.
• To extend the applicability of marker-based motion tracking to non-laboratory environments.

Main Methods:

• A correction algorithm was developed to identify camera vibrations using specialized target positions.
• 2D shift vectors (Δw) were calculated by comparing dynamic and static target positions.
• Individual camera streams were corrected using the derived shift vectors.
• The algorithm was tested on a four-camera system with separate and simultaneous perturbations.

Main Results:

• The correction algorithm significantly reduced reconstruction residuals to the level of calibration residuals in cases of individual camera perturbation.
• Accurate 3D motion reconstruction was achieved even when multiple cameras were simultaneously perturbed, a feat impossible without correction.
• The method demonstrated robustness in reducing vibration effects on motion capture data.

Conclusions:

• The proposed correction algorithm effectively addresses camera vibrations in 3D motion capture systems.
• This technique expands the utility of marker-based infrared motion tracking to dynamic and accelerated camera setups.
• The approach facilitates more versatile and real-world applications of motion capture technology.