Real-time moving obstacle detection using optical flow models

In this paper, we propose a real-time method to detect obstacles using theoretical models of optical flow fields. The idea of our approach is to segment the image in two layers: the pixels which match our optical flow model and those that do not (i.e. the obstacles). In this paper, we focus our approach on a model of the motion of the ground plane. Regions of the visual field that violate this model indicate potential obstacles. In the first part of this paper, we will describe the method we used to determine our model of the ground plane's motion. Then we will focus on the method to match both the model and the real optical flow field. Experiments have been carried on the Cycab mobile robot in real-time on a standard PC laptop.