On-demand transmission of 3D models over lossy networks

Tian, Dongdong; AlRegib, Ghassan

doi:10.1016/j.image.2006.01.003

Cited by 14 publications

(10 citation statements)

References 21 publications

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“…Error concealment is considered by Park et al [22]. Cheng et al [9] argue for retransmissions as the main error control method, while Tian [24] uses selective retransmission in their system.…”

Section: Streaming Of 3d Datamentioning

confidence: 99%

Peer-assisted view-dependent progressive mesh streaming

Cheng

Liú

Ooi

2009

Proceedings of the 17th ACM International Conference on Multimedia

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Progressive mesh streaming is increasingly used in 3D networked applications, such as online games, virtual worlds, and digital museums. To scale such applications to a large number of users without high infrastructure cost, we apply peer-to-peer techniques to mesh streaming. We consider two issues: how to partition a progressive mesh into chunks and how to lookup the provider of a chunk. For the latter issue, we investigated into two solutions, which trade off server overhead and response time. The first uses a simple centralized lookup service, while the second organizes peers into groups according to the hierarchical structure of the progressive meshes to take advantage of access pattern. Simulation results show that our proposed systems are robust under high churn rate, reduce the server overhead by more than 90%, keep control overhead below 10%, and achieve low average response time.

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Section: Streaming Of 3d Datamentioning

confidence: 99%

Peer-assisted view-dependent progressive mesh streaming

Cheng

Liú

Ooi

2009

Proceedings of the 17th ACM International Conference on Multimedia

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“…Three-dimensional meshes are a common representation for geometry and many recent works focus on how to transmit them in a progressive and robust way over bandlimited lossy channels [2,3]. An alternate common solution, specially used in free viewpoint video, is to represent texture by a set of images (or videos) of the scene and geometry by depth maps.…”

Section: Introductionmentioning

confidence: 99%

“…Several methods have been proposed for the robust transmission of 3D models over lossy channels [3,[8][9][10] and of course many others exist for the transmission of image (texture) data [11]. However the combined transmission of both kinds of data over lossy channels is still a quite unexplored field.…”

Section: Introductionmentioning

confidence: 99%

Transmission of 3D Scenes over Lossy Channels

Zanuttigh

Zanella

Maguolo

et al. 2010

International Journal of Digital Multimedia Broadcasting

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This paper introduces a novel error correction scheme for the transmission of three-dimensional scenes over unreliable networks. We propose a novel Unequal Error Protection scheme for the transmission of depth and texture information that distributes a prefixed amount of redundancy among the various elements of the scene description in order to maximize the quality of the rendered views. This target is achieved exploiting also a new model for the estimation of the impact on the rendered views of the various geometry and texture packets which takes into account their relevance in the coded bitstream and the viewpoint required by the user. Experimental results show how the proposed scheme effectively enhances the quality of the rendered images in a typical depth-image-based rendering scenario as packets are progressively decoded/recovered by the receiver.

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“…This would lead to a significant visual degradation in model rendering. To enable error recovery, methods including Forward Error Correction (FEC) coding [3] , Equal Error Protection (EEP) [4] , Unequal Error Protection (UEP) [4] , hybrid UEP and Selective Retransmission [5] have been proposed. FEC [3] is designed to correct bit errors in individual model packet.…”

Section: Introductionmentioning

confidence: 99%

An Effective Error Resilient Packetization Scheme for Progressive Mesh Transmission over Unreliable Networks

Yang

Pan

et al. 2008

J. Comput. Sci. Technol.

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When a 3D model is transmitted over a lossy network, some model information may inevitably be missing. Under such situation, one may not be able to visualize the receiving model unless the lost model information has been retransmitted. Progressive model transmission offers an alternative to avoid the "all or nothing situation" by allowing a model to be visualized with a degraded quality when only part of the model data has been received. Unfortunately, in case some model refinement information is missing, one may still need to wait for such information to be retransmitted before the model can be rendered with a desired visual quality. To address this problem, we have developed a novel error resilient packetization scheme. We first construct a Non-Redundant Directed Acyclic Graph to encode the dependencies among the vertex splits of a progressive mesh. A special Global Graph Equipartition Packing Algorithm is then applied to partitioning this graph into several equal size sub-graphs, which is packed as packets. The packing algorithm comprises two main phases: initial partition phase and global refinement phase. Experimental results demonstrate that the proposed scheme can minimize the dependencies between packets. Hence, it reduces the delay in rendering 3D models with proper quality at the clients.

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On-demand transmission of 3D models over lossy networks

Cited by 14 publications

References 21 publications

Peer-assisted view-dependent progressive mesh streaming

Peer-assisted view-dependent progressive mesh streaming

Transmission of 3D Scenes over Lossy Channels

An Effective Error Resilient Packetization Scheme for Progressive Mesh Transmission over Unreliable Networks

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