Time-of-flight (ToF) cameras are a novel, fast, and robust means for intra-operative 3D surface acquisition. They acquire surface information (range images) in real-time. In the intra-operative registration context, these surfaces must be matched to pre-operative CT or MR surfaces, using so called descriptors, which represent surface characteristics. We present a framework for local and global multi-modal comparison of surface descriptors and characterize the differences between ToF and CT data in an in vitro experiment. The framework takes into account various aspects related to the surface characteristics and does not require high resolution input data in order to establish appropriate correspondences. We show that the presentation of local and global comparison data allows for an accurate assessment of ToF-CT discrepancies. The information gained from our study may be used for developing ToF pre-processing and matching algorithms, or for improving calibration procedures for compensating systematic distance errors. The framework is available in the open-source platform Medical Imaging Interaction Toolkit (MITK).