Binaural technology is often used for the reproduction of virtual sound images. The principle of binaural technology is to control the sound field at the listener's ears so that the reproduced sound field coincides with the desired real sound field. For the implementation of binaural technology over loudspeakers, it is necessary to cancel the cross-talk that prevents a signal meant for one ear from being heard at the other. However, such cross-talk cancellation, normally realized by time-invariant filters, works only for a specific listening location and the sound field can only be controlled in a limited area refereed to as the ‘’sweet-spot’’. If the listener moves away from the optimal listening location, it is required that the inverse filters are updated so that the sweet-spot is steered to the listener's new location. The issues related to filter updates have been investigated intensively in this work.

The aim of this project is to find a way to improve filter update techniques as well as to determine the filter update rate necessary to stabilize an acoustic image regardless of listener movement. This work is based on the assumption that the location of the listener is known from a visual head tracking device.

The effectiveness of cross-talk cancellation depends on the geometry of the system and in theory each frequency band can be reproduced from a loudspeaker pair with an optimal source span. Therefore the concept of Frequency Distributed Loudspeakers (FDLs) has been studied, and the idea is to reproduce each frequency from an optimal source angle within a given listening area.

The area that the listener can move within when the filters are updated can be determined by introducing the concept of ‘’operational area’’. Hence, the operational area represents the region where the ‘’sweet-spot’’ can be moved within using an adaptive virtual sound system. The extent of the operational area depends on performance criteria and is investigated thoroughly.

The relatively small ‘’sweet-spot’’ of a static virtual sound imaging system, creates strong demand for an effective head tracking algorithm within the field of virtual sound. Adding access to a video camera for the audio system gives the possibility to track head movements and update the inverse filters accordingly. The increasing interest in visual tracking is due in part to the falling cost of computing power, video cameras and memory. A sequence of images grabbed at or near video rate typically does not change radically from frame to frame, and this redundancy of information over multiple images can be extremely helpful for analysing the input, in order to track individual objects.