Nighttime Pedestrian Detection with Near Infrared using Cascaded Classifiers

This paper presents a novel nighttime pedestrian detection approach only using a near infrared camera, which can be used in a practical driver assistance systems. This method can be divided into three steps: selection step, preprocess step and recognition step. Firstly, objects in the video are separated with an adaptive dual thresholds segmentation method in the selection step; Secondly, most of non-pedestrians are discarded with some constraints in the preprocess step; Finally, in the recognition step a cascaded classifiers with Histograms of Oriented Gradients and Adaptive Boosting Algorithm are introduced. Experiments on video sequences show that the proposed pedestrian detection approach has a high detection rate as well as a very low false alarm rate and run in real-time.