3-D Audio in Mobile Communication Devices: Methods for Mobile Head-Tracking

Future generations of mobile communication devices will serve more and more as multimedia platforms capable of reproducing high quality audio. In order to achieve a 3-D sound perception the reproduction quality of audio via headphones can be significantly increased by applying binaural technology. To be independent of individual head-related transfer functions (HRTFs) and to guarantee a good performance for all listeners, an adaptation of the synthesized sound field to the listener's head movements is required. In this article several methods of head-tracking for mobile communication devices are presented and compared. A system for testing the identified methods is set up and experiments are performed to evaluate the prosand cons of each method. The implementation of such a device in a 3-D audio system is described and applications making use of such a system are identified and discussed.

Head Tracking Based Avatar Control for Virtual Environment Teamwork Training

Virtual environments (VE) are gaining in popularity and are increasingly used for teamwork training purposes, e.g., for medical teams. One shortcoming of modern VEs is that nonverbal communication channels, essential for teamwork, are not supported well. We address this issue by using an inexpensive webcam to track the user's head. This tracking information is used to control the head movement of the user's avatar, thereby conveying head gestures and adding a nonverbal communication channel. We conducted a user study investigating the influence of head tracking based avatar control on the perceived realism of the VE and on the performance of a surgical teamwork training scenario. Our results show that head tracking positively influences the perceived realism of the VE and the communication, but has no major influence on the training outcome.

Application of Time-Delay Estimation to Mixed Reality Multisensor Tracking

Spatial tracking is one of the most challenging and important parts of Mixed Reality environments. Many applications, especially in the domain of Augmented Reality, rely on the fusion of several tracking systems in order to optimize the overall performance. While the topic of spatial tracking sensor fusion has already seen considerable interest, most results only deal with the integration of carefully arranged setups as opposed to dynamic sensor fusion setups. A crucial prerequisite for correct sensor fusion is the temporal alignment of the tracking data from several sensors. Tracking sensors are typically encountered in Mixed Reality applications, are generally not synchronized. We present a general method to calibrate the temporal offset between different sensors by the Time Delay Estimation method which can be used to perform on-line temporal calibration. By applying Time Delay Estimation on the tracking data, we show that the temporal offset between generic Mixed Reality spatial tracking sensors can be calibrated. To show the correctness and the feasibility of this approach, we have examined different variations of our method and evaluated various combinations of tracking sensors. We furthermore integrated this time synchronization method into our UBITRACK Mixed Reality tracking framework to provide facilities for calibration and real-time data alignment.