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

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 ± 0.55 compared to the initial configuration with -0.07 ± 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.

Authors

Publication Details

Published
2024-10-14
DOI
https://doi.org/10.1109/iros58592.2024.10801852
Citations
1
Primary Topic
Human Motion and Animation
Type
article
Field-Weighted Citation Impact
0.33

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Amartya Ganguly, Junnan Li, Sami Haddadin, Christopher Herneth et al.
1 citations
Human Motion and Animation
0.33
article

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

Amartya Ganguly, Junnan Li, Sami Haddadin, Christopher Herneth, Muhammad Hilman Fatoni, Fajar Budiman
article en
1 citations

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 ± 0.55 compared to the initial configuration with -0.07 ± 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.

Ministry of Education
Affordable and clean energy
Openalex Percentile: Top 38%
Human Motion and Animation
0.33
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.