Development of an on-board pedestrian detection system using monocular camera for driver assistance applications

Abstract

Recent statistical data of traffic accidents reveals that pedestrian fatalities are a particular priority in Europe and Japan. Many active safety systems for pedestrian protection based on sensor fusion approach such as millimeter wave radar, Laser Imaging Detecting And Ranging (LIDAR) and monocular/stereo camera are proposed. Aiming at large-scale system penetration in automobile markets, low-cost driver assistance system development becomes an important issue, therefore a monocular camera is one of solutions. To realize zero-traffic accident society, the objective of this paper is to develop a driver assistance system for pedestrian collision prevention based on using a monocular camera. As the concept of the system, moving objects on and nearby a crosswalk are interpreted as pedestrians. An on-board camera image processing algorithm is designed to detect the existence of a crosswalk in front of the vehicle. The feature extraction technique used in the algorithm is based on the feature called "cross ratio" of the crosswalk edges and the periodicity of the crosswalk paints. Then, nearby the detected crosswalk position, the region of interest is determined to be used in the moving object detection module. The position and the velocity of the moving object are obtained with the application of optical flow algorithm. Crosswalk image database in real-world traffic in Japan is constructed, and the precision of crosswalk detection is examined by using the database. Optical flow algorithm is applied on the region nearby the detected crosswalk in order to detect moving objects which are inferred as pedestrians. Image-based egomotion estimation is used to compensate the error in distance estimation and pedestrian movement. The effectiveness of the proposed system is verified by test drives. The system can perform the detection of crosswalks in urban area in various weather conditions with high detection rate. Pedestrians on crosswalks can also be detected by Optical Flow-based image processing algorithm. The detectable range of the proposed pedestrian detection with crosswalk detection function is 20-25 m in front of vehicle. This approach does not claim to cover 100% of all pedestrian accidents, but has the advantage of high robustness, low false alarm rate and cost efficient implementation. The feasibility of the proposed camera-based pedestrian detection system is shown in the paper. The validation of the crosswalk detection and pedestrian detection algorithm using real-world driving database will be conducted and demonstrated in the full paper. © Springer-Verlag 2013.