On-Board Pedestrian and Cyclist Recognition Using Deep Learning Methods

In recent years, the application of advanced driver assistance systems (ADAS) has improved road safety. However, unlike motor vehicle drivers, pedestrians, cyclists, and other vulnerable road users have been given less attention. Most existing pedestrian and cyclist recognition methods recognize them separately, which often leads to confusion between the two classes. Also, the limited capability of traditional object recognition models makes them difficult to apply in complicated road environments. This paper establishes a unified framework for pedestrian and cyclist concurrent recognition, with relevant key technologies in the recognizing process, including multiple-instance object proposal method, deep neural network-based object detection, and multiple object tracking with online target-specific self-learning function. Experimental results indicate that the proposed pedestrian and cyclist concurrent recognition …