A scalable lane detection algorithm on COTSs with OpenCL

Road lane detection are classical requirements for advanced driving assistant systems. With new computer technologies, lane detection algorithms can be exploited on COTS platforms. This paper investigates the use of OpenCL and develop a particle-filter based lane detection algorithm that can tune the trade-off between detection accuracy and speed. Our algorithm is tested on 14 video streams from different data-sets with different scenarios on different COTS hardware. With an average deviation fewer than 5 pixels, the average frame rates for the 14 videos can reach about 400 fps on both GPU and FPGA. The peak frame rates for certain videos on GPU can reach almost 1000 fps.