Thorsten Dr. Graf

Pedestrian detection in infrared images

This paper describes an approach for pedestrian detection in infrared images. The developed system has been implemented on an experimental vehicle equipped with an infrared camera and preliminarily tested in different situations. It is based on the localization of warm symmetrical objects with specific size and aspect ratio; since also road infrastructures and other road participants may have such characteristics, a set of matched filters was added in order to reduce false detections. A final validation process, based on the human shapes morphological characteristics, is used to build the list of pedestrian appearing in the scene. No temporal correlation, nor motion cues are used in this first part of the project.

A modular tracking system for far infrared pedestrian recognition

This paper describes a modular tracking system designed to improve the performance of a pedestrian detector. The tracking system consists of two modules, a labeler and a predictor. The former associates a tracking identifier to each pedestrian, keeping memory of the past history; this is achieved by merging the detector and predictor outputs combined with data about vehicle motion. The predictor, basically a Kalman filter, estimates the new pedestrian position by observing his previous movements. Its output helps the labeler to improve the match between the pedestrians detected in the new frame and those observed in the previous shots (feedback). If a pedestrian is occluded by some obstacle for a short while, the system continues tracking its movement using motion parameters. Moreover, it is able to reassign the same tracking ID in case the occlusion disappears in a short time. This behavior helps to correct temporary mis-recognitions that occur when the detector fails. The system has been tested using a quantitative performance evaluation tool, giving promising results.

A software video stabilization system for automotive oriented applications

Vision applications in the vehicular technology field can take big advantages by electronic stabilization of video sequences since it reduces calibration based feature measurement and tracking errors. In this paper a new video stabilization system expressly designed for automotive applications is presented. Image correction is fast and can be included in real time applications. The system has been implemented on one of the vehicles in use at the Department of Information Technology of the University of Parma and tested in a wide range of cases. A test using a vision based pedestrian detector is presented as case study showing promising improvements in detection rate.