Modelled object pose estimation and tracking by a multi-cameras system

Our paper proposes a new model based approach to locate and track an object in a multi-cameras system: this method does not involve triangulation. If the calibration and the mutual geometry of the acquisition systems are known, it is possible to express the whole set of equations pertaining to each monocular system, in an unique reference system. In this way it is possible to show that based model methods are not restricted to monocular vision and that some techniques generally viewed as purely monocular can be readily extended and integrated to a multi-cameras system. We prove by experiments on sequences of real images that this approach leads to results better than the monocular ones in two directions: better accuracy as many different view points are used; better robustness as the system is able to deal gracefully with the loss of some of the captors