Reconstruction error in a motion capture system

TL;DR

This paper analyzes the reconstruction error in marker-based motion capture systems, proposing an efficient approximation method to understand how different camera configurations affect accuracy.

Contribution

It introduces a novel approximation of the reconstruction error variance that reduces computational time while accurately predicting error behavior in MoCap systems.

Findings

The approximation closely matches actual error variance in simulations.

The method significantly reduces computational complexity.

It provides insights into optimal camera configurations for MoCap.

Abstract

Marker-based motion capture (MoCap) systems can be composed by several dozens of cameras with the purpose of reconstructing the trajectories of hundreds of targets. With a large amount of cameras it becomes interesting to determine the optimal reconstruction strategy. For such aim it is of fundamental importance to understand the information provided by different camera measurements and how they are combined, i.e. how the reconstruction error changes by considering different cameras. In this work, first, an approximation of the reconstruction error variance is derived. The results obtained in some simulations suggest that the proposed strategy allows to obtain a good approximation of the real error variance with significant reduction of the computational time.