Robust and Scalable Transmission of Arbitrary 3D Models over Wireless Networks

We describe transmission of 3D objects represented by texture and mesh over unreliable networks, extending our earlier work for regular mesh structure to arbitrary meshes and considering linear versus cubic interpolation. Our approach to arbitrary meshes considers stripification of the mesh and distributing nearby vertices into different packets, combined with a strategy that does not need texture or mesh packets to be retransmitted. Only the valence (connectivity) packets need to be retransmitted; however, storage of valence information requires only 10% space compared to vertices and even less compared to photorealistic texture. Thus, less than 5% of the packets may need to be retransmitted in the worst case to allow our algorithm to successfully reconstruct an acceptable object under severe packet loss. Even though packet loss during transmission has received limited research attention in the past, this topic is important for improving quality under lossy conditions created by shadowing and interference. Results showing the implementation of the proposed approach using linear, cubic, and Laplacian interpolation are described, and the mesh reconstruction strategy is compared with other methods

In-Network View Synthesis for Interactive Multiview Video Systems

To enable Interactive multiview video systems with a minimum view-switching delay, multiple camera views are sent to the users, which are used as reference images to synthesize additional virtual views via depth-image-based rendering. In practice, bandwidth constraints may however restrict the number of reference views sent to clients per time unit, which may in turn limit the quality of the synthesized viewpoints. We argue that the reference view selection should ideally be performed close to the users, and we study the problem of in-network reference view synthesis such that the navigation quality is maximized at the clients. We consider a distributed cloud network architecture where data stored in a main cloud is delivered to end users with the help of cloudlets, i.e., resource-rich proxies close to the users. In order to satisfy last-hop bandwidth constraints from the cloudlet to the users, a cloudlet re-samples viewpoints of the 3D scene into a discrete set of views (combination of received camera views and virtual views synthesized) to be used as reference for the synthesis of additional virtual views at the client. This in-network synthesis leads to better viewpoint sampling given a bandwidth constraint compared to simple selection of camera views, but it may however carry a distortion penalty in the cloudlet-synthesized reference views. We therefore cast a new reference view selection problem where the best subset of views is defined as the one minimizing the distortion over a view navigation window defined by the user under some transmission bandwidth constraints. We show that the view selection problem is NP-hard, and propose an effective polynomial time algorithm using dynamic programming to solve the optimization problem. Simulation results finally confirm the performance gain offered by virtual view synthesis in the network