A GPU-based Algorithm for Estimating 3D Geometry and Motion in Near Real-time

Real-time 3D geometry and motion estimation has many important applications in areas such as robot navigation and dynamic image-based rendering. A novel algorithm is proposed in this paper for estimating 3D geometry and motion of dynamic scenes based on captured stereo sequences. All computations are conducted in the 2D image space of the center view and the results are represented in forms of disparity maps and disparity flow maps. A dynamic programming based technique is used for searching global optimal disparity maps and disparity flow maps under an energy minimization framework. To achieve high processing speed, most operations are implemented on the Graphics Processing Units (GPU) of programmable graphics hardware. As a result, the derived algorithm is capable of producing both 3D geometry and motion information for dynamic scenes in near real-time. Experiments on two trinocular stereo sequences demonstrate that the proposed algorithm can handle scenes that contain non-rigid motion as well as those captured by moving cameras.