Real-time modeling of dynamic environments in traffic scenarios using a stereo-vision system

Real-time modeling of dynamic environments is one of the most demanding research problems in the field of driving assistance systems. The representation module may be affected by several factors such as occlusions, unpredictable nature of the traffic participants, wrong associations or noisy measurements. In this paper we propose two different methods for real-time modeling of dynamic environments. Both motion estimation techniques are vision-based and rely on information provided by a Digital Elevation Map. The first approach consists in determining the differences between the previous and current frames. These differences are then used for computing the speeds of the traffic participants. The second motion estimation technique consists in using a fast pairwise alignment of object delimiters that are extracted by radial scanning of the Elevation Map. The final result is a more compact polygonal map with associated static and dynamic features.