Obstacle Detection and Pedestrian Recognition Using A 3D PMD Camera

This paper presents a 3D-camera system and appropriate algorithms for the image processing to provide pedestrian recognition. According to international legislative proposals the automotive industry is forced to take action in the area of protecting vulnerable road users. The presented photonic mixer device (PMD) sensor system is able to fulfil specific requirements of a pedestrian protection assistant. It consists of a sensor with a resolution of 64 times 16 pixel, lightsources, and the image processing unit. The light emitting diodes (LEDs) of the lightsources emit a modulated signal in the infrared (IR) spectrum. The sensor calculates the object distance by means of the phase of the reflected signal. The range of the system is approximately 15 m for pedestrians and up to 30 m for objects with high reflectivity, e.g. cars with number plates. The horizontal field-of-view is 55deg. The presented image processing unit consists of two main steps. In the first step both a robust and efficient segmentation method is performed to create reliable detections of the objects and a useful description of their projection in the image plane. It uses the linking pyramid method regarding the partition of the distance image and a contour-based grouping algorithm, where the objects are described using the chain code representation. In the second step a classification of the resulting objects is carried out. Depending on the distance of the objects which have to be classified a shape- or motion-based verification is applied adaptively. Both approaches discussed in this paper deliver very good results at the corresponding distance and represent a solid foundation of further works