Viewpoint-popularity-driven uplink scheduling of multi-camera sensor arrays

A decentralized camera array records a 3D scene of interest simultaneously, from different perspectives. The captured video signals need to be transmitted over a shared wireless channel to a central station. The gathered data is then streamed to a collection of clients interested in experiencing the scene interactively. I design an optimization framework that allows for sharing the transmission resources of the wireless medium such that the average video quality over the client population is maximized. I consider scheduling the uplink resources either at the view or packet level. That is, in the first case, the central station partitions the channel capacity across a select subset of views that are transmitted in their entirety. In the second case, the station coordinates the packet transmissions of every sensor such that the aggregate data rate over the wireless channel does not exceed its capacity. I formulate algorithms that solve the optimization either exactly or approximatively, at lower complexity. I examine their transmission efficiency via simulation experiments that show a considerable improvement over reference methods. I also study the impact of viewpoint popularity, as governed by the clients that interact with the scene, on the operation of the optimization.