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An Audio-Visual Method for Room Boundary Estimation and Material Recognition

Remaggi, Luca, Jackson, Philip J. B., Kim, Hansung and Hilton, Adrian (2018) An Audio-Visual Method for Room Boundary Estimation and Material Recognition In: 2018 Workshop on Audio-Visual Scene Understanding for Immersive Multimedia (AVSU’18), 22-26 Oct 2018, Seoul, Korea.

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Abstract

In applications such as virtual and augmented reality, a plausible and coherent audio-visual reproduction can be achieved by deeply understanding the reference scene acoustics. This requires knowledge of the scene geometry and related materials. In this paper, we present an audio-visual approach for acoustic scene understanding. We propose a novel material recognition algorithm, that exploits information carried by acoustic signals. The acoustic absorption coefficients are selected as features. The training dataset was constructed by combining information available in the literature, and additional labeled data that we recorded in a small room having short reverberation time (RT60). Classic machine learning methods are used to validate the model, by employing data recorded in five rooms, having different sizes and RT60s. The estimated materials are utilized to label room boundaries, reconstructed by a visionbased method. Results show 89 % and 80 % agreement between the estimated and reference room volumes and materials, respectively.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Remaggi, Lucal.remaggi@surrey.ac.uk
Jackson, Philip J. B.P.Jackson@surrey.ac.uk
Kim, HansungH.Kim@surrey.ac.uk
Hilton, AdrianA.Hilton@surrey.ac.uk
Date : 2018
Identification Number : 10.1145/3264869.3264876
Copyright Disclaimer : © 2018 Association for Computing Machinery. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from permissions@acm.org.
Uncontrolled Keywords : Audio-Visual; Material Recognition; Room Boundary Estimation; KNN; Acoustic Absorption Coefficient
Related URLs :
Depositing User : Clive Harris
Date Deposited : 13 Aug 2018 14:24
Last Modified : 13 Aug 2018 14:24
URI: http://epubs.surrey.ac.uk/id/eprint/848909

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