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Visual simultaneous localisation and mapping (SLAM) is since the last decades an often addressed problem. Online mapping enables tracking in unknown environments. However, it also suffers from high computational complexity and potential drift. Moreover, in augmented reality applications the map itself is often not needed and the target environment is partially known, e.g. in a few 3D anchor or marker...
The use of a particle filter (PF) for camera pose estimation is an ongoing topic in the robotics and computer vision community, especially since the FastSLAM algorithm has been utilised for simultaneous localisation and mapping (SLAM) applications with a single camera. The major problem in this context consists in the poor proposal distribution of the camera pose particles obtained from the weak motion...
We present a new visual-inertial tracking device for augmented and virtual reality applications. The paper addresses two fundamental issues of such systems. The first one concerns the definition and modelling of the sensor fusion. Much work has been done in this area and several models for exploiting the data of the gyroscopes and linear accelerometers have been proposed. However, the respective advantages...
In this paper we introduce a novel architecture for rapid development and assessment of advanced 3D visual tracking systems. Indeed, we notice that it does not exist up to now a universal tracking approach that fulfills the requirements of all possible application scenarios at the same time. On contrary, very specific and performing solutions can be developed for given situations and uses. Therefore,...
One of the key requirements of augmented reality systems is a robust real-time camera pose estimation. In this paper we present a robust approach, which does neither depend on offline pre-processing steps nor on pre-knowledge of the entire target scene. The connection between the real and the virtual world is made by a given CAD model of one object in the scene. However, the model is only needed for...
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