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On the way to achieving higher degrees of autonomy for vehicles in complicated, ever changing scenarios, the localization problem poses a very important role. Especially the Simultaneous Localization and Mapping (SLAM) problem has been studied greatly in the past. For an autonomous system in the real world, we present a very cost-efficient, robust and very precise localization approach based on GraphSLAM...
Autonomous driving has become a focus for many universities and automotive companies alike, aiming for public introduction within the next few years. However, this requires assurance that the inherent risk in critical systems such as localization is sufficiently low. In aviation, the concept of integrity was established for this purpose. It relies upon a localization system's ability to provide timely...
Pedestrian detection is a rapidly evolving area in the intelligent vehicles domain. Stereo vision is an attractive sensor for this purpose. But unlike for monocular vision, there are no realistic, large scale benchmarks available for stereo-based pedestrian detection, to provide a common point of reference for evaluation. This paper introduces the Daimler Stereo-Vision Pedestrian Detection benchmark,...
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