Affine Colour Optical Flow Computation

Abstract

The purpose of this paper is three-fold. First, we develop an algorith for the computation a locally affine optical flow field from multichannel images as an extension of the Lucus-Kanade (LK) method. The classical LK method solves a system of linear equations assuming that the flow field is locally constant. Our method solves a collection of systems of linear equations assuming the flow field is locally affine. For autonomous navigation in a real environment, the adaptation of the motion and image analysis algorithm to illumination changes is a fundamental problem, because illumination changes in an image sequence yield counterfeit obstacles. Second, we evaluate the colour channel selection of colour optical flow computation. By selecting an appropriate colour channel, it is possible to avoid these counterfeit obstacle regions in the snapshot image in front of a vehicle. Finally, we introduce an evaluation criterion for the computed optical flow field without ground truth.