The scene flow in binocular stereo setup is estimated using a seed growing algorithm. A pair of calibrated and synchronized cameras observe a scene and output a sequence of images. The algorithm jointly computes a disparity map between the stereo images and optical flow maps between consecutive frames. Having the calibration, this is a representation of the scene flow, i.e. a 3D velocity vector is associated with each reconstructed 3D point. The proposed algorithm starts from correspondence seeds and propagates the correspondences to the neighborhood. It is accurate for complex scenes with large motion and produces temporally coherent stereo disparity and optical flow results. The algorithm is fast due to inherent search space reduction.