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Recently, impressive results have been reported for the detection of objects in challenging real-world scenes. Interestingly however, the underlying models vary greatly even between the most successful approaches. Methods using a global feature descriptor (e.g. [1]) paired with discriminative classifiers such as SVMs enable high levels of performance, but(More)
A variety of flexible models have been proposed to detect objects in challenging real world scenes. Motivated by some of the most successful techniques, we propose a hierarchical multi-feature representation and automatically learn flexible hierarchical object models for a wide variety of object classes. To that end we not only rely on automatic selection(More)
Object recognition is challenging due to high intra-class variability caused, e.g., by articulation, viewpoint changes, and partial occlusion. Successful methods need to strike a balance between being flexible enough to model such variation and discriminative enough to detect objects in cluttered, real world scenes. Motivated by these challenges we propose(More)
Finding injured humans is one of the primary goals of any search and rescue operation. The aim of this paper is to address the task of automatically finding people lying on the ground in images taken from the on-board camera of an unmanned aerial vehicle (UAV). In this paper we evaluate various state-of-the-art visual people detection methods in the context(More)
In urban search and rescue scenarios, typical applications of robots include autonomous exploration of possibly dangerous sites, and the recognition of victims and other objects of interest. In complex scenarios, relying on only one type of sensor is often misleading, while using complementary sensors frequently helps improving the performance. To that end,(More)
The Darmstadt Rescue Robot Team is a new team established from a PhD program funded by the German Research Foundation at TU Darmstadt. It combines expertise from Computer Science and Mechanical Engineering. Several team members have already contributed in the past to highly successful teams in the RoboCup four-legged and hu-manoid leagues.
The team Hector Darmstadt has been established from a PhD program funded by the German Research Foundation at TU Darm-stadt. It combines expertise from Computer Science and Mechanical Engineering. In 2009 the team successfully participated for the first time in the RoboCup rescue league. Several team members have already contributed in the past to highly(More)
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