An attention-guided algorithm for improving the performance of acoustic simulations
(2019) p.2619-2626- Abstract
- When performing acoustic simulations with the purpose of auralization, there is a trade-off between accuracyand speed. In real-time simulations of virtual reality, finding the balance of this trade-off is paramount to achiev-ing the desired result. If successful, the simulation speed is sufficient to provide a seamless acoustic experienceas the agent moves around the space, while still being accurate enough to be realistic. It is generally acceptedthat a 20ms update interval for the impulse response is sufficient for achieving proper interactivity in mostapplications. However, reaching this threshold without degrading the quality of simulation too badly can bechallenging indeed for complex scenes.In this paper, a... (More)
- When performing acoustic simulations with the purpose of auralization, there is a trade-off between accuracyand speed. In real-time simulations of virtual reality, finding the balance of this trade-off is paramount to achiev-ing the desired result. If successful, the simulation speed is sufficient to provide a seamless acoustic experienceas the agent moves around the space, while still being accurate enough to be realistic. It is generally acceptedthat a 20ms update interval for the impulse response is sufficient for achieving proper interactivity in mostapplications. However, reaching this threshold without degrading the quality of simulation too badly can bechallenging indeed for complex scenes.In this paper, a compromise between interactivity (response time) and accuracy is suggested for raytracing simu-lations. This compromise mimics the behaviour of the listener or the agent, prioritizing speed or accuracy basedon how the agent behaves. When the listener is actively moving around the space, interactivity is prioritized.When the listener stands still, fully immersing in the experience, accuracy is improved. This is achieved byexploiting a fundamental truth of Monte Carlo simulations: Convergence improves with more samples (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/0b603bda-1376-48fe-837f-3c93630dfa3c
- author
- Autio, Hanna LU and Bard, Delphine LU
- organization
- publishing date
- 2019-09
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proceedings of the 23rd International Congress on Acoustics : integrating 4th EAA Euroregio 2019 : 9-13 September 2019 in Aachen, Germany
- pages
- 2619 - 2626
- publisher
- Deutsche Gesellschaft für Akustik
- external identifiers
-
- scopus:85099329244
- ISBN
- 978-3-939296-15-7
- DOI
- 10.18154/RWTH-CONV-239586
- language
- English
- LU publication?
- yes
- id
- 0b603bda-1376-48fe-837f-3c93630dfa3c
- date added to LUP
- 2021-01-26 10:10:46
- date last changed
- 2022-04-19 04:30:09
@inproceedings{0b603bda-1376-48fe-837f-3c93630dfa3c, abstract = {{When performing acoustic simulations with the purpose of auralization, there is a trade-off between accuracyand speed. In real-time simulations of virtual reality, finding the balance of this trade-off is paramount to achiev-ing the desired result. If successful, the simulation speed is sufficient to provide a seamless acoustic experienceas the agent moves around the space, while still being accurate enough to be realistic. It is generally acceptedthat a 20ms update interval for the impulse response is sufficient for achieving proper interactivity in mostapplications. However, reaching this threshold without degrading the quality of simulation too badly can bechallenging indeed for complex scenes.In this paper, a compromise between interactivity (response time) and accuracy is suggested for raytracing simu-lations. This compromise mimics the behaviour of the listener or the agent, prioritizing speed or accuracy basedon how the agent behaves. When the listener is actively moving around the space, interactivity is prioritized.When the listener stands still, fully immersing in the experience, accuracy is improved. This is achieved byexploiting a fundamental truth of Monte Carlo simulations: Convergence improves with more samples}}, author = {{Autio, Hanna and Bard, Delphine}}, booktitle = {{Proceedings of the 23rd International Congress on Acoustics : integrating 4th EAA Euroregio 2019 : 9-13 September 2019 in Aachen, Germany}}, isbn = {{978-3-939296-15-7}}, language = {{eng}}, pages = {{2619--2626}}, publisher = {{Deutsche Gesellschaft für Akustik}}, title = {{An attention-guided algorithm for improving the performance of acoustic simulations}}, url = {{http://dx.doi.org/10.18154/RWTH-CONV-239586}}, doi = {{10.18154/RWTH-CONV-239586}}, year = {{2019}}, }