Title:
Panoptic reconstruction of immersive virtual soundscapes using human-scale panoramic imagery with visual recognition
Panoptic reconstruction of immersive virtual soundscapes using human-scale panoramic imagery with visual recognition
Author(s)
Huang, Mincong (Jerry)
Chabot, Samuel
Braasch, Jonas
Chabot, Samuel
Braasch, Jonas
Advisor(s)
Editor(s)
Collections
Supplementary to
Permanent Link
Abstract
This work, situated at Rensselaer's Collaborative-Research Augmented Immersive Virtual Environment Laboratory (CRAIVELab), uses panoramic image datasets for spatial audio display. A system is developed for the room-centered immersive virtual reality facility to analyze panoramic images on a segment-by-segment basis, using pre-trained neural network models for semantic segmentation and object detection, thereby generating audio objects with respective spatial locations. These audio objects are then mapped with a series of synthetic and recorded audio datasets and populated within a spatial audio environment as virtual sound sources. The resulting audiovisual outcomes are then displayed using the facility's human-scale panoramic display, as well as the 128-channel loudspeaker array for wave field synthesis (WFS). Performance evaluation indicates effectiveness for real-time enhancements, with potentials for large-scale expansion and rapid deployment in dynamic immersive virtual environments.
Sponsor
Date Issued
2021-06
Extent
Resource Type
Text
Resource Subtype
Proceedings
Rights Statement
Licensed under Creative Commons Attribution Non-Commercial 4.0 International License.