Optimizing Interaction Space: Enlarging the Capture Volume for Multiple Portable Motion Capture Devices

TL;DR

This study enhances the tracking volume of multiple Leap Motion Controllers to improve hand kinematics measurement accuracy, but dynamic movement measurement remains challenging despite increased interaction space.

Contribution

It introduces an optimized layout for multiple LMCs using Monte Carlo simulation to enlarge capture volume and improve measurement reliability.

Findings

Optimized LMC configuration improves visibility rate.

Multiple LMCs increase interaction space but struggle with dynamic movements.

Validation against MMC shows improved but still limited accuracy.

Abstract

Markerless motion capture devices such as the Leap Motion Controller (LMC) have been extensively used for tracking hand, wrist, and forearm positions as an alternative to Marker-based Motion Capture (MMC). However, previous studies have highlighted the subpar performance of LMC in reliably recording hand kinematics. In this study, we employ four LMC devices to optimize their collective tracking volume, aiming to enhance the accuracy and precision of hand kinematics. Through Monte Carlo simulation, we determine an optimized layout for the four LMC devices and subsequently conduct reliability and validity experiments encompassing 1560 trials across ten subjects. The combined tracking volume is validated against an MMC system, particularly for kinematic movements involving wrist, index, and thumb flexion. Utilizing calculation resources in one computer, our result of the optimized configuration has a better visibility rate with a value of 0.05 $\pm$ 0.55 compared to the initial configuration with -0.07 $\pm$ 0.40. Multiple Leap Motion Controllers (LMCs) have proven to increase the interaction space of capture volume but are still unable to give agreeable measurements from dynamic movement.