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An experimental comparison of ‘Edge-Element Association (EEA)’ and ‘Marginalized Contour (MCo)’ approaches for 3D model-based vehicle tracking in traffic scenes is complicated by the different shape and motion models with which they have been implemented originally. It is shown that the steering-angle motion model originally associated with EEA allows more robust tracking than the angular-velocity...
3D-model-based tracking offers one possibility to explicate the manner in which spatial coherence can be exploited for the analysis of image sequences. Two seemingly different approaches towards 3D-model-based tracking are compared using the same digitized video sequences of road traffic scenes. Both approaches rely on the evaluation of greyvalue discontinuities, one based on a hypothesized probability...
This article describes the robot Stanley, which won the 2005 DARPA Grand Challenge. Stanley was developed for high-speed desert driving without human intervention. The robot’s software system relied predominately on state-of-the-art AI technologies, such as machine learning and probabilistic reasoning. This article describes the major components of this architecture, and discusses the results of the...
This article presents the architecture of Junior, a robotic vehicle capable of navigating urban environments autonomously. In doing so, the vehicle is able to select its own routes, perceive and interact with other traffic, and execute various urban driving skills including lane changes, U-turns, parking, and merging into moving traffic. The vehicle successfully finished and won second place in the...
Motris, an integrated system for model-based tracking research, has been designed modularly to study the effects of algorithmic variations on tracking results. Motris attempts to avoid introducing bias into the relative assessment of alternative approaches. Such a bias may be caused by differences of implementation and parameterization if the component approaches are evaluated in separate testing...
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