A Compact Representation of the Head-Related Transfer Function Inspired by the Wavelet Transform on the Sphere

Jorge Alberto Trevino Lopez, Shichao Hu, Cesar Daniel Salvador Castaneda, Shuichi Sakamoto, Junfeng Li, Yoiti Suzuki

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

The head-related transfer function (HRTF) characterizes the propagation of sound from its source to the listener's ears. It is commonly used in the research of spatial sound and its applications. The HRTF takes different values depending on the source's position relative to the listener and its frequency. Storing its values directly results in considerably large data sets. Previous research to encode the HRTF using harmonic functions cannot handle local features efficiently. This paper advances a new analysis method to represent raw HRTF data using local functions of the azimuth and elevation angles. The proposal treats features of different scales separately, in a manner similar to the wavelet transform. This allows us to compress HRTF data considerably while accurately preserving its features at all scales. The proposal yields better accuracy than harmonic analysis methods for the finer spatial patterns, this holds even when our method uses more aggressive compression.

Original languageEnglish
Title of host publicationProceedings - 2015 International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages372-375
Number of pages4
ISBN (Print)9781509001880
DOIs
Publication statusPublished - 2016 Feb 19
Event11th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015 - Adelaide, Australia
Duration: 2015 Sep 232015 Sep 25

Other

Other11th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2015
CountryAustralia
CityAdelaide
Period15/9/2315/9/25

Keywords

  • compression
  • functions on the sphere
  • head-related transfer function
  • wavelet transform

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing
  • Artificial Intelligence
  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality

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