Monovision-based vehicle detection, distance and relative speed measurement in urban traffic

This study presents a monovision-based system for on-road vehicle detection and computation of distance and relative speed in urban traffic. Many works have dealt with monovision vehicle detection, but only a few of them provide the distance to the vehicle which is essential for the control of an intelligent transportation system. The system proposed integrates a single camera reducing the monetary cost of stereovision and RADAR-based technologies. The algorithm is divided in three major stages. For vehicle detection, the authors use a combination of two features: the shadow underneath the vehicle and horizontal edges. They propose a new method for shadow thresholding based on the grey-scale histogram assessment of a region of interest on the road. In the second and third stages, the vehicle hypothesis verification and the distance are obtained by means of its number plate whose dimensions and shape are standardised in each country. The analysis of consecutive frames is employed to calculate the relative speed of the vehicle detected. Experimental results showed excellent performance in both vehicle and number plate detections and in the distance measurement, in terms of accuracy and robustness in complex traffic scenarios and under different lighting conditions

Walking Pedestrian Recognition

In recent years a lot of methods providing the ability to recognize rigid obstacles-like sedans and trucks have been developed. These methods mainly provide driving relevant information to the driver. They are able to cope reliably with scenarios on motor-ways. Nevertheless, not much attention has been given to image processing approaches to increase safety of pedestrians in traffic environments. In this paper a method for detection, tracking, and final classification of pedestrians crossing the moving observer's trajectory is suggested. Herein a combination of data and model driven approaches is realized. The initial detection process is based on a texture analysis and a model-based grouping of most likely geometric features belonging to a pedestrian on intensity images. Additionally, motion patterns of limb movements are analyzed to determine initial object hypotheses. For this tracking of the quasi-rigid part of the body is performed by different trackers that have been successfully employed for tracking of sedans, trucks, motor-bikes, and pedestrians. The final classification is obtained by a temporal analysis of the walking process

An Image Processing System for Driver Assistance

Systems for automated image analysis are useful for a variety of tasks. Their importance is still growing due to technological advances and increased social acceptance. Especially driver assistance systems have reached a high level of sophistication. Fully or partly autonomously guided vehicles, particularly for road traffic, require highly reliable algorithms due to the conditions imposed by natural environments. At the Institut für Neuroinformatik, methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We present a system extracting important information from an image taken by a CCD camera installed at the rear-view mirror in a car. The approach is divided into a sequential and a parallel phase of sensor and information processing. Three main tasks, namely initial segmentation (object detection), object tracking and object classification are realized by integration in the sequential phase and by fusion in the parallel phase. The main advantage of this approach is integrative coupling of different algorithms providing partly redundant information

Ein hochsprachenprogrammierbares System zur Vollbildauswertung im Videotakt, Anwendungen zur Interpretation monokularer, semi-strukturierter Bildfolgen bei natürlicher Beleuchtung und schnell bewegter Kamera

Im vorliegenden Beitrag wird ein hochsprachenprogrammierbares System zur schritthaltenden Vollbild-Interpretation natürlich beleuchteter Szenenfolgen im Videotakt vorgestellt. Im einzelnen werden folgende Teilmodule und Subsysteme beschrieben: eine hochdynamische, pixellokal autoadaptive CMOS-Kamera mit ca. 120 dB Helligkeitsdynamik (20Bits/Pixel), ein hochsprachenprogrammierbarer Systolic Array Prozessor (für die pixelbezogenen Verarbeitungsmodule) im PCI-Kartenformat, samt optimierendem Compiler, Simulator und Emulator, Systemprozeßgerüste unter Linux auf den für die Echtzeit-Anwendungen eingesetzten Hostrechnern (z.B. DEC/Alpha oder Intel/Pentium), eine prototypische Anwendung zur bildverarbeitungsbasierten Eigenbewegungsbeobachtung (Translationsrichtung, Rotationsraten), eine prototypische, automotive Anwendung zur schritthaltenden Detektion und Kartierung des Straßen- und Spurverlaufs unter partieller monokularer 3D-Rekonstruktion, sowie prototypische Anwendungen zur Klassifikatio n verkehrsrelevanter Hindernisse (Verkehrsteilnehmer)