ICOIN '01 Proceedings of the The 15th International Conference on Information Networking
Coordinated multi-streaming for 3D tele-immersion
Proceedings of the 12th annual ACM international conference on Multimedia
TEEVE: The Next Generation Architecture for Tele-immersive Environment
ISM '05 Proceedings of the Seventh IEEE International Symposium on Multimedia
IEEE Transactions on Parallel and Distributed Systems
ViewCast: view dissemination and management for multi-party 3d tele-immersive environments
Proceedings of the 15th international conference on Multimedia
MM '08 Proceedings of the 16th ACM international conference on Multimedia
Multicast routing with end-to-end delay and delay variation constraints
IEEE Journal on Selected Areas in Communications
DVBMN-l: delay variation bounded multicast network with multiple paths
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
SyncCast: synchronized dissemination in multi-site interactive 3D tele-immersion
MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
Synchronized dissemination framework for supporting high-quality tele-immersive shared activity
MM '11 Proceedings of the 19th ACM international conference on Multimedia
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The 3D tele-immersive and collaborative environment provides a virtual space for the interaction of remotely dispersed users. To achieve multi-perspective rendering and realistic 3D visual effect, it is needed to transmit multiple semantically correlated 3D video streams from the source to the destination with stringent synchronization requirement. In this paper we discuss the issue of multi-stream synchronization from the general context of the multicast routing with delay and delay variation constraints, which was proved as an NP-complete problem. Then we propose a heuristic to construct a multicast network on an overlay content dissemination architecture for the solution, and show that our algorithm is asymptotically more advanced in the time complexity than existing ones. Empirical studies further verify the performance of our algorithm regarding to the temporal efficiency in various sizes of input data.