Since Head Mounted Displays (HMD), datagloves, tracking systems, and powerful computer graphics resources are nowadays in an affordable price range, the usage of PC-based "Virtual Training Systems" becomes very attractive. However, due to the limited field of view of HMD devices, additional modalities have to be provided to benefit from 3D environments. A 3D sound simulation can improve the capabilities of VR systems dramatically. Unfortunately, realistic 3D sound simulations are expensive and demand a tremendous amount of computational power to calculate reverberation, occlusion, and obstruction effects. To use 3D sound in a PC-based training system as a way to direct and guide trainees to observe specific events in 3D space, a cheaper alternative has to be provided, so that a broader range of applications can take advantage of this modality. To address this issue, we focus in this paper on the evaluation of a low-cost 3D sound simulation that is capable of providing traceable 3D sound events. We describe our experimental system setup using conventional stereo headsets in combination with a tracked HMD device and present our results with regard to precision, speed, and used signal types for localizing simulated sound events in a virtual training environment.
Previous experiences during earthquake events emphasize the need for new technologies for real-time monitoring and assessment of facilities with high value nonstructural elements such as equipment or other contents. Moreover, there are substantial limitations to our ability to rapidly evaluate and identify potential hazard zones within a structure, exposing rescue workers, society and the environment to unnecessary risks. A real-time monitoring system, integrated with critical warning systems, would allow for improved channeling of resources. Ideally such a system would acquire all relevant data non-intrusively, at high rates and resolution and disseminate it with low latency over a trusted network to a central repository. This repository can then be used by the building owner and rescue workers to make informed decisions. In recognition of these issues, in this paper, we describe a methodology for image-based tracking of seismically induced motions. The methodology includes calibration, acquisition, processing, and analysis tools geared towards seismic assessment. We present sample waveforms extracted considering pixel-based algorithms applied to images collected from an array of high speed, highresolution charged-couple-device (CCD) cameras. This work includes use of a unique hardware and software design involving a multi-threaded process, which bypasses conventional hardware frame grabbers and uses a software-based approach to acquire, synchronize and time stamp image data.
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