Zdenek Prochazka, National Institute of Technology, Japan

In recent years, many researchers and car makers put a lot of intensive effort into development of autonomous driving systems. Since visual information is the main modality used by human driver, a camera mounted on moving platform is very important kind of sensor, and various computer vision algorithms to handle vehicle surrounding situation are under intensive research. Our final goal is to develop a vision based lane detection system with ability to handle various types of road shapes, working on both structured and unstructured roads, ideally under presence of shadows. This paper presents a modified road region segmentation algorithm based on sequential Monte-Carlo estimation. Detailed description of the algorithm is given, and evaluation results show that the proposed algorithm outperforms the segmentation algorithm developed as a part of our previous work, as well as an conventional algorithm based on colour histogram.

Lane Recognition, Road Region Segmentation, Sequential Monte-Carlo Estimation