This work addresses the video synchronization problem, which consists in finding the temporal alignment between sequences of images acquired with unsynchronized cameras. This problem has been addressed before, under the assumptions that the cameras are static or jointly moving and that there are correspondences between the features visible in the different sequences. There are some methods in the literature that managed to drop one of these assumptions, but none of them was successful in getting rid of both assumptions simultaneously. In this work, we introduce a new strategy that synchronizes cameras that are allowed to move freely even when there are no correspondences between the features that are visible in the different sequences. Our approach consists in tracking features on two rigid objects that move independently on the scene and use the relative motion between them as a clue for the synchronization. New synchronization algorithms for static or jointly moving cameras that see (possibly) different parts of a common rigidly moving object are also presented. Even though the emphasis of this work is essentially on the theoretical contribution of the proposed methods, rather than on an exhaustive experimental validation, several proof of concept experiments conducted with both real and synthetic data are presented. In the case of static or jointly moving cameras, comparisons with a state-of-the-art approach are also provided.

In this paper, new methodologies for the estimation of the depth of a target with unknown dimensions, based on depth from focus strategies, are proposed. The image-based measurements are detailed, through the minimization of a new functional, deeply rooted on optical characteristics of the lens system, namely the point spread function. This work complements an inexpensive single pan and tilt camera-based indoor positioning and tracking system, resorting to complementary filters for depth estimation. A motivation example is provided, where the target dimensions are assumed as known. Then, an extension corresponding to an higher-order filter is presented, that tackles the problem at hand. To assess the performance of the proposed system, a series of indoor experimental tests for a range of operation of up to ten meter were carried out. A centimetric accuracy was obtained under realistic conditions.