We derive an optimization framework for computing a view selection policy for streaming multi-view content over a bandwidth constrained channel. The optimization allows us to determine the decisions of sending the packetized data such that the end-to-end reconstruction quality of the content is maximized, for the given bandwidth resources. Two prospective multi-view content representation formats are considered: MVC and video plus depth. For each, we formulate directed graph models that characterize the interdependencies between the data units comprising the content. For the video plus depth format, we develop a spatial error concealment strategy that reconstructs missing content at the client based on received data from other views. We design multiple techniques to solve the optimization problem of interest either exactly or approximatively, at lower complexity. In conjunction, we derive a spatial model of the reconstruction error for the multi-view content that we employ to reduce the computational requirements of the optimization. We study the performance of our framework via simulation experiments. Significant gains in terms of rate-distortion efficiency are observed over a content-agnostic reference technique.