Room Geometry Estimation from Acoustic Echoes using Graph-Based Echo Labeling

Room Geometry Estimation from Acoustic Echoes using Graph-Based Echo Labeling

Jager, Ingmar (Student TU Delft)
Heusdens, R. (TU Delft Signal Processing Systems)
Gaubitch, N.D. (TU Delft Signal Processing Systems)

Dong, Min (editor)
Zheng, Thomas Fang (editor)

2016-05-19

A computer being able to estimate the geometry of a room could benefit applications such as auralization, robot navigation, virtual reality and teleconferencing. When estimating the geometry of a room using multiple microphones, the main challenge is to identify which reflections, or echoes, originate from the same wall and can, therefore, be modeled by a virtual source outside the room using the mirror image source model. In this paper we present a new and efficient method to disambiguate the echoes using a graph theoretical approach where echo combinations are modeled as nodes in a graph and the problem is stated as a maximum independent set problem. Once the echoes are correctly labelled, we know the locations of the virtual sources from which we can infer the room geometry. Experiments for shoe-box shaped rooms show that we can reliably estimate the room geometry within seconds on contemporary hardware and achieve centimeter precision on finding the vertices of the room.

independent sets
room geometry estimation
mirror image source model

http://resolver.tudelft.nl/uuid:c0b3c9f6-b5bf-4030-bcf6-635424a27819

https://doi.org/10.1109/icassp.2016.7471625

IEEE, Danvers, MA

978-1-4799-9988-0

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP): Proceedings

2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016, 2016-03-20 → 2016-03-25, Shanghai International Convention Center, Shanghai, China

Winner Best Student Paper Award track audio and acoustic signal processing

Institutional Repository

conference paper

© 2016 Ingmar Jager, R. Heusdens, N.D. Gaubitch