Annealed Particle Filter Algorithm Used for Lane Detection and Tracking

This paper describes a lane detection and tracking method based on annealed particle filter algorithm, which combines multiple cues with annealed particle filter. As a first step, preprocessing, with bar filter and color cues being used. In the annealed particle filter step, angle information of edge map is utilized to measure weights of particles. Experiments show that the time cost of annealed particle filter algorithm for each frame is largely reduced comparing with the lane detection and tracking using conventional particle filter algorithm, which is the main contribution of this paper. Furthermore, on this basis, we build a robust lane model which can be applied to not only the linear road but also the curved road. The experiments indicate that it is effective for lane detection and tracking. 

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