A comparative study of stereo-matching algorithms for road-modeling in the presence of windscreen wipers

In this study we examine three road-modeling methods, which we evaluate on seven stereo matching algorithms. The road-modeling methods we consider are a B-spline modeling technique based on region-growing and two versions of the popular v-disparity approach. The used stereo algorithms are variations or different parameterizations of belief propagation, graph cut and semi-global matching. We examine the performance of the possible combinations of modeling methods and stereo algorithms by comparing the deviation towards a reference road profile. Two evaluation sequences are used, of which one features switched on windscreen wipers that are visible in the the recorded imagery. Our findings are that the examined B-spline modeling method provides the best results in most cases. In terms of the modeled distance, belief propagation is the most suitable stereo matching method, which also performs best with the wiper sequence. Semi global matching achieves smaller model deviations, but with drastically reduced modeled distances.