Audio-Visual Calibration with Polynomial Regression for 2-D Projection Using SVD-PHAT

François Grondin; Hao Tang; James R. Glass

ICASSP 2020accepted0 citations

Audio-Visual Calibration with Polynomial Regression for 2-D Projection Using SVD-PHAT

François Grondin, Hao Tang, James R. Glass

Abstract

This paper proposes a straightforward 2-D method to spatially calibrate the visual field of a camera with the auditory field of an array microphone by generating and overlaying an acoustic image over an optical image. Using a low-cost microphone array and an off-the-shelf camera, we show that polynomial regression can deal efficiently with non-linear camera distortion, and that a recently proposed sound source localization method for real-time processing, SVD-PHAT, can be adapted for this task.

BibTeX

@inproceedings{icassp2020_audiovisualcalib,
  title = {Audio-Visual Calibration with Polynomial Regression for 2-D Projection Using SVD-PHAT},
  author = {François Grondin and Hao Tang and James R. Glass},
  booktitle = {ICASSP 2020},
  year = {2020}
}