Two-frame frequency-based estimation of local motion parallax direction in 3D cluttered scenes

When an observer moves in a 3D static scene, the resulting motion field depends on the depth of the visible objects and on the observer's instantaneous translation and rotation. It is well-known that the vector difference - or motion parallax - between nearby image motion field vectors points toward the direction of heading and so computing this vector difference can help in estimating the heading direction. For 3D cluttered scenes that contain many objects at many different depths, it can be difficult to compute local image motion vectors because these scenes have many depth discontinuities which corrupt local motion estimates and thus it is unclear how to estimate local motion parallax. Recently a frequency domain method was proposed to address this problem which uses the space-time power spectrum of a sequence of images. The method requires a large number of frames, however, and assumes the observer's motion is constant within these frames. Here we present a frequency-based method which uses two frames only and hence does not suffer from the limitations of the previously proposed method. We demonstrate the effectiveness of the new method using both synthetic and natural images.