TY - CHAP A1 - Herder, Jens T1 - Optimization of Sound Spatialization Resource Management through Clustering T2 - Second International Conference on Human and Computer N2 - Level-of-detail is a concept well-known in computer graphics to reduce the number of rendered polygons. Depending on the distance to the subject (viewer), the objects’ representation is changed. A similar concept is the clustering of sound sources for sound spatialization. Clusters can be used to hierarchically organize mixels and to optimize the use of resources, by grouping multiple sources together into a single representative ource. Such a clustering process should minimize the error of position allocation of elements, perceived as angle and distance, and also differences between velocity relative to the sink (i.e., Doppler shift). Objects with similar direction of motion and speed (relative to sink) in the same acoustic resolution cone and with similar distance to a sink can be grouped together. KW - audio rendering KW - clustering, and human perception KW - Resource Management KW - Sound Spatialization Y1 - 1999 SP - 1 EP - 7 CY - Aizu-Wakamatsu ER - TY - JOUR A1 - Herder, Jens T1 - Visualization of a Clustering Algorithm of Sound Sources based on Localization Errors JF - Journal of the 3D-Forum Society N2 - A module for soundscape monitoring and visualizing resource management processes was extended for presenting clusters, generated by a novel sound source clustering algorithm. This algorithm groups multiple sound sources together into a single representative source, considering localization errors depending on listener orientation. Localization errors are visualized for each cluster using resolution cones. Visualization is done in runtime and allows understanding and evaluation of the clustering algorithm. KW - audio rendering, clustering KW - human perception KW - Resource Management KW - Sound Spatialization KW - Visualization Y1 - 1999 VL - 13 IS - 3 SP - 66 EP - 70 ER - TY - CHAP A1 - Herder, Jens T1 - Visualization of a Clustering Algorithm of Sound Sources based on Localization Errors T2 - Second International Conference on Human and Computer N2 - A module for soundscape monitoring and visualizing resource management processes was extended for presenting clusters, generated by a novel sound source clustering algorithm. This algorithm groups multiple sound sources together into a single representative source, considering localization errors depending on listener orientation. Localization errors are visualized for each cluster using resolution cones. Visualization is done in runtime and allows understanding and evaluation of the clustering algorithm. KW - audio rendering, clustering KW - human perception KW - Resource Management KW - Sound Spatialization KW - Visualization Y1 - 1999 SP - 1 EP - 5 CY - Aizu-Wakamatsu ER -