In telepresence applications each user is immersed in a rendered 3D-world composed from representations transmitted from remote sites. The challenge is to compute dense range data at high frame rates, since participants cannot easily communicate if the processing cycle or network latencies are long. Moreover, errors in new stereoscopic views of the remote 3D-world should be hardly perceptible. To achieve the required speed and accuracy, we use trinocular stereo, a matching algorithm based on the sum of modified normalized cross-correlations, and subpixel disparity interpolation. To increase speed we use Intel IPL functions in the pre-processing steps of background subtraction and image rectification as well as a four-processor parallelization. To evaluate our system we have developed a testbed which provides a set of registered dense "ground-truth" laser data and image data from multiple views.