For the examination of mixing processes in turbulent flows a system based on a high-speed solid state camera has been implemented, which allows for the quasi-simultaneous acquisition of sequences of flow tomography voxel data. In these data, velocity fields are determined by 3D least squares matching. The first part of the paper will show a hardware configuration based on a highspeed solid state camera with a maximum frame rate of 500 images per second and a scanning laser lightsheet, which allows for the acquisition of flow tomography data sequences with a typical size of 256 × 256 × 50 voxels per volume dataset at a rate of 10 datasets per second. The quality of the data and some special problems of the highspeed camera will be discussed. In the second part of the paper the 3D implementation of least squares matching with a 12-parameter 3D affine transformation between voxel-patches of consecutive datasets will be described. In order to strengthen the matching in regions with insufficient local contrast the algorithm is combined with several geometric and radiometric constraints.