Optical flow computation is one of the most important tasks in computer vision. The article deals with a modification of the variational method of the optical flow computation, according to its application in stereo vision. Such approaches are traditionally based on a brightness constancy assumption and a gradient constancy assumption during pixels motion. Smoothness assumption also restricts motion discontinuities, i.e. the smoothness of the vector field of pixel velocity is assumed. It is proposed to extend the functional of the optical flow computation in a similar way by adding a priori known stereo cameras extrinsic parameters and minimize such jointed model of optical flow computation. The article presents a partial differential equations framework in image processing and numerical scheme for its implementation. Performed experimental evaluation demonstrates that the proposed method gives smaller errors than traditional methods of optical flow computation.
Efficient Optical Flow and Stereo Vision for Velocity Estimation and Obstacle Avoidance on an Autonomous Pocket Drone
