On visual crosswalk detection for driver assistance systems

In this paper a new crosswalk detection strategy is presented. The application area is narrowed down to driver assistance systems to guarantee a reliable detection result and to benefit from the properties of a vehicle mounted camera. The main contribution of this paper is an efficient method to detect line segments that are typical for road markings like lanes and crosswalks. Therefore an adaptive Haar-like filter is applied by means of an integral image, where the pass-band of the filter is adjusted according to the distance from the vehicle. The detected segments are then combined to regions of interest by means of prior knowledge of crosswalk dimensions. These regions are then passed to a simple classifying module that utilizes a set of moment invariants for classification. The final detection result is then tracked by a standard Kalman filter.