A Novel Real Time Pedestrian Detection System on Monocular Vision
Accuracy and speed are the two important keys in pedestrian detection. In order to balance these two indexes well, this thesis presents a novel pedestrian detection system, ROIs cascaded Uniform LBP and improved HOG, for real time pedestrian detection in monocular vision. Two contributions are made in this system. First contribution is that Uniform LBP (Local Binary Pattern) cascaded improved HOG (Histograms of Oriented Gradients) are the novel structure for pedestrian detection, which can improve detection speed. Second contribution is that this pedestrian detection system is evaluated by many methods and algorithms. Experiment shows that this system can deal with 31 fps, which can be used as the real time pedestrian detection system.