Observing the Clustering Tendencies of Head Related Transfer Function Databases
Areti Andreopoulou, Agnieszka Rogińska, Juan Pablo Bello · Journal of the Audio Engineering Society · 2011
This study offers a detailed description of the clustering tendencies of a large, standardized HRTF repository, and compares the quality of the results to those of a CIPIC database subset. The statistical analysis was implemented by applying k-means clustering on the log magnitude of HRTFs on the horizontal plane, for a varying number of clusters. A thorough report on the grouping behavior of the filters as the number of clusters increases revealed a superiority of the HRTF repository in describing common behaviors across equivalent azimuth positions, over the CIPIC subset, for the majority of the HRTF datasets.