A saliency-based cascade method for fast traffic sign detection

We propose a cascade method for fast and accurate traffic sign detection. The main feature of the method is that mid-level saliency test is used to efficiently and reliably eliminate background windows. Fast feature extraction is adopted in the subsequent stages for rejecting more negatives. Combining with neighbor scales awareness in window search, the proposed method runs at 3~5 fps for high resolution (1360×800) images, 2~7 times as fast as most state-of-the-art methods. Compared with them, the proposed method yields competitive performance on prohibitory signs while sacrifices performance moderately on danger and mandatory signs.