Ulrich Brunsmann

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This paper focuses on real-time pedestrian detection on Field Programmable Gate Arrays (FPGAs) using the Histograms of Oriented Gradients (HOG) descriptor in combination with a Support Vector Machine (SVM) for classification as a basic method. We propose to process image data at twice the pixel frequency and to normalize blocks with the L1-Sqrt-norm(More)
We present a real-time multi-sensor architecture for video-based pedestrian detection used within a road side unit for intersection assistance. The entire system is implemented on available PC hardware, combining a frame grabber board with embedded FPGA and a graphics card into a powerful processing network. Giving classification performance top priority,(More)
This paper focuses on stat ionary detect ion of the pedestrian's intention to enter the traffic lane at intersections. We use an Interacting Multiple Model Extended Kalman Filter (IMM-EKF) based tracking approach as basic method to recognize this. In addition, we propose a novel Motion Contour image based HOG-like descriptor (MCHOG) in combination with(More)
To significantly reduce injury and fatal accidents smart intersections equipped with sensors and communication infrastructure have been proposed. In this publication a novel multi sensor network to perceive the intersection environment is presented. Based on an intensive analysis of accident scenarios in Germany the system was designed to address 75 % of(More)
PURPOSE To evaluate the thermal load of ablation in high-speed laser corneal refractive surgery with the AMARIS excimer laser (SCHWIND eye-tech-solutions). METHODS Thermal load from refractive corrections on human corneas using a 500-Hz laser system with a fluence of 500 mJ/cm(2) and aspheric ablation profiles was recorded with an infrared thermography(More)
This paper focuses on monocular-video-based stationary detection of the pedestrian's intention to enter the traffic lane. We propose a motion contour image based HOG-like descriptor, MCHOG, and a machine learning algorithm that reaches the decision at an accuracy of 99% within the initial step at the curb of smart infrastructure. MCHOG implicitly comprises(More)
We present a real-time multisensor architecture for combined laser scanner and infra-red video-based pedestrian detection and tracking used within a road side unit for intersection assistance. In order to achieve outmost classification performance we propose a cascaded classifier using laser scanner hypothesis generation and histogram of oriented gradients(More)
This paper focuses on the early prediction of a pedestrian's short time trajectory in the course of gait initiation at a crosswalk. We present a comprehensive study on trajectories of adults measured at a public urban intersection using 3D triangulation of stationary video-based marker- and head-detection data. Based on the results of this study we propose(More)
We present an active pedestrian protection system that performs an autonomous lane-keeping evasive maneuver in urban traffic scenarios when collision avoidance by braking is no longer possible. The system focuses on pedestrians standing at the curb and intending to cross the street despite an approaching car. It is demonstrated that the evasive maneuver of(More)
Cooperative traffic safety is a straightforward approach for a significant reduction of accidents and fatalities. This paper presents a predictive safety system based on a cooperative localization technology using transponders combined with a monocular camera. By means of these sensor components other traffic partners in the surrounding area are recognized(More)