Audio-aided Character Control for Inertial Measurement Tracking

Simple item page
dc.contributor.authorJang, Hojunen_US
dc.contributor.authorBae, Jinseoken_US
dc.contributor.authorKim, Young Minen_US
dc.contributor.editorCeylan, Duyguen_US
dc.contributor.editorLi, Tzu-Maoen_US
dc.date.accessioned2025-05-09T09:36:19Z
dc.date.available2025-05-09T09:36:19Z
dc.date.issued2025
dc.description.abstractPhysics-based character control generates realistic motion dynamics by leveraging kinematic priors from large-scale data within a simulation engine. The simulated motion respects physical plausibility, while dynamic cues like contacts and forces guide compelling human-scene interaction. However, leveraging audio cues, which can capture physical contacts in a costeffective way, has been less explored in animating human motions. In this work, we demonstrate that audio inputs can enhance accuracy in predicting footsteps and capturing human locomotion dynamics. Experiments validate that audio-aided control from sparse observations (e.g., an IMU sensor on a VR headset) enhances the prediction accuracy of contact dynamics and motion tracking, offering a practical auxiliary signal for robotics, gaming, and virtual environments.en_US
dc.description.sectionheadersShort Paper 4
dc.description.seriesinformationEurographics 2025 - Short Papers
dc.identifier.doi10.2312/egs.20251045
dc.identifier.isbn978-3-03868-268-4
dc.identifier.issn1017-4656
dc.identifier.pages4 pages
dc.identifier.urihttps://doi.org/10.2312/egs.20251045
dc.identifier.urihttps://diglib.eg.org/handle/10.2312/egs20251045
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectCCS Concepts: Computing methodologies → Simulation by animation; Physical simulation; Motion processing
dc.subjectComputing methodologies → Simulation by animation
dc.subjectPhysical simulation
dc.subjectMotion processing
dc.titleAudio-aided Character Control for Inertial Measurement Trackingen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
egs20251045.pdf
Size:
839.34 KB
Format:
Adobe Portable Document Format
Download
Collections
EG 2025 - Short Papers