Greedy alternative for room geometry estimation from acoustic echoes: a subspace-based method

Mario Coutino, Martin Bo Møller, Jesper Kjær Nielsen, Richard Heusdens

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

8 Citations (Scopus)


In this paper, we present a greedy subspace method for the acoustic echoes labeling problem, which occurs in applications such as source localization and room geometry estimation. The orthogonal projection into the null space of the microphones position matrix is used to filter and sort all possible combinations of echoes. A greedy strategy, based on the rank constraint of Euclidean distance matrices (EDMs), is used on the sorted subset of echo combinations to extract the feasible combinations. Numerical simulations using room impulse responses (RIRs) from shoe-box shaped rooms show that the method provides improvements in terms of computational complexity and the number of required measurements with respect to a recently published graph-based method.
Original languageEnglish
Title of host publication2017 International Conference on Acoustics, Speech, and Signal Processing - Proceedings
Place of PublicationPiscataway, NJ
Number of pages5
ISBN (Electronic)978-1-5090-4117-6
Publication statusPublished - 2017
EventICASSP 2017: 42nd IEEE International Conference on Acoustics, Speech and Signal Processing - The Internet of Signals - Hilton New Orleans Riverside, New Orleans, LA, United States
Duration: 5 Mar 20179 Mar 2017
Conference number: 42


ConferenceICASSP 2017
Abbreviated titleICASSP
Country/TerritoryUnited States
CityNew Orleans, LA
Internet address


  • acoustic echoes
  • room geometry
  • sorting reflections
  • greedy algorithm
  • source localization


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