In this paper, we propose a unified calibration technique for a heterogeneous sensor network of video camcorders and Time-of- Flight (ToF) cameras. By moving a spherical calibration target around the commonly observed scene, we can robustly and conveniently extract the sphere centers in the observed images and recover the geometric extrinsics for both types of sensors. The approach is then evaluated with a real dataset of two HD camcorders and two ToF cameras, and 3D shapes are reconstructed from this calibrated system. The main contributions are: (1) We reveal the fact that the frontmost sphere surface point to the ToF camera center is always highlighted, and use this idea to extract sphere centers in the ToF camera images; (2) We propose a unified calibration scheme in spite of the heterogeneity of the sensors. After the calibration, this multi-modal sensor network thus becomes powerful to generate high-quality 3D shapes efficiently.