In this paper, we propose a new recursive framework for camera resectioning and apply it to off-line video-based augmented reality. Our algorithm is based on an unscented particle filter, which deals with non-linear dynamic systems without local linearization, and leads to more accurate results than other non-linear filters. The proposed approach has some desirable properties. It does not rely ...

In this paper, the problem of tracking cooperative mobile nodes in wireless sensor networks is addressed. Aiming at an efficient resource solution, the research adopts a strategy of combining target tracking with node selection procedures in order to select informative sensors to minimize the energy consumption of the tracking task. We layout a clusterbased architecture to address the limitatio...

In the Standard Platform League (SPL) there are substantial sensor limitations due to the rapid motion of the camera, the limited field of view of the camera, and the limited number of unique landmarks. These limitations place high demands on the performance and robustness of localization algorithms. Most of the localization algorithms implemented in RoboCup fall broadly into the class of parti...

Selecting conveniently the proposal kernel and the adjustment multiplier weights of the auxiliary particle filter may increase significantly the accuracy and computational efficiency of the method. However, in practice the optimal proposal kernel and multiplier weights are seldom known. In this paper we present a simulation-based method for constructing offline an approximation of these quantit...

Nonlinear filtering is an important standard tool for information and sensor fusion applications, e.g., localization, navigation, and tracking. It is an essential component in surveillance systems and of increasing importance for standard consumer products, such as cellular phones with localization, car navigation systems, and augmented reality. This thesis addresses several issues related to n...