2015
DOI: 10.1109/taslp.2015.2419971
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Novel Sampling Scheme on the Sphere for Head-Related Transfer Function Measurements

Abstract: This paper presents a novel sampling scheme on the sphere for obtaining head-related transfer function (HRTF) measurements and accurately computing the spherical harmonic transform (SHT). The scheme requires an optimal number of samples, given by the degrees of freedom in the spectral domain, for the accurate representation of the HRTF that is band-limited in the spherical harmonic domain. The proposed scheme allows for the samples to be easily taken over the sphere due to its iso-latitude structure and non-de… Show more

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Cited by 27 publications
(35 citation statements)
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References 35 publications
(123 reference statements)
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“…10(a) and 10(b). This is because Fourier-Legendre transforms are applied along two hemi-circumferences separated by the interaural axis and, unfortunately, differ- Overall accuracies obtained with the method in interaural coordinates, calculated with (13) and (14), are displayed in Fig. 12.…”
Section: Resultsmentioning
confidence: 99%
See 3 more Smart Citations
“…10(a) and 10(b). This is because Fourier-Legendre transforms are applied along two hemi-circumferences separated by the interaural axis and, unfortunately, differ- Overall accuracies obtained with the method in interaural coordinates, calculated with (13) and (14), are displayed in Fig. 12.…”
Section: Resultsmentioning
confidence: 99%
“…Resulting overall accuracies of the proposal in spherical coordinates, calculated with (13) and (14), are displayed in Fig. 13.…”
Section: Resultsmentioning
confidence: 99%
See 2 more Smart Citations
“…Recently, a perceptual study [22] has reported that low-order HRTF representations might be sufficient to approximate an individual space, whereas an objective study [23] has identified HRTF features that would require high-order representations. Because the required resolution for characterizing an individual space is still an open question, the performance of binaural systems should be evaluated by considering HRTF datasets with the higher resolution that can be achieved.…”
Section: Introductionmentioning
confidence: 99%