Thomas Michalke

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— Several Advanced Driver Assistance Systems realizing elementary perception and analysis tasks have been introduced to market in recent years. For example, collision mitigation brake systems detect the distance and relative velocity of vehicles in front to assess the risk of a rear-end collision in a clearly defined following situation. In order to go(More)
Biologically motivated attention systems prefilter the visual environment for scene elements that pop out most or match the current system task best. However, the robustness of biological attention systems is difficult to achieve, given e.g., the high variability of scene content, changes in illumination, and scene dynamics. Most computational attention(More)
— Currently available traffic sign recognition systems typically focus on a single class of traffic sign and therefore, the algorithms are optimized to find only this specific class. To this end, a number of approaches for real time capable classification of mostly circular signs exist. Nevertheless, to simultaneously recognize a number of classes a(More)
Research on computer vision systems for driver assistance resulted in a variety of approaches mainly performing reactive tasks like, e.g., lane keeping. However, for a full understanding of generic traffic situations , integrated and more flexible approaches are needed. We present a system inspired by the human visual system. Based on combining(More)
The use of computer vision for assisting the driver dates back to first research projects in the 80's, but only recently the progress in vision research and the increase in computational power have resulted in actual products. Although impressive from the robustness point of view, these systems are optimized for specific problems and at best perform(More)
Research on computer vision systems for driver assistance resulted in a variety of isolated approaches mainly performing very specialized tasks like, e. g., lane keeping or traffic sign detection. However, for a full understanding of generic traffic situations, integrated and flexible approaches are needed. We here present a highly integrated vision(More)
— In this paper we propose a system architecture that extends the current state-of-the-art in computational visual attention by incorporating the biological concept of ventral attention. According to recent findings regarding the neuro-biological foundations of attention, there exist two separate but interacting attention systems in the human brain: the(More)