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Applying the machine-learning technique of inference in Markov random fields we build improved 3D models by integrating two different modalities. Visual input from a standard color camera delivers high-resolution texture data but also enables us to enhance the 3D data calculated from the range output of a 3D time-of-flight camera in terms of noise and spatial resolution. The proposed method to increase the visual quality of the 3D data makes this kind of camera a promising device for various upcoming 3DTV applications. With our two-camera setup we believe that the design of low-cost, fast and highly portable 3D scene acquisition systems will be possible in the near future.