An analytical model for progressive mesh streaming

Cheng, Wei; Ooi, Wei Tsang; Grigoras, Romulus; Morin, Géraldine

doi:10.1145/1291233.1291399

Cited by 29 publications

(26 citation statements)

References 16 publications

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“…Noticing that in both Figure 3 and Figure 4, distortions do not change linearly, we believe it is related with vertices' importance. As mentioned in [5,7], every split vertex has an importance value and there are dependencies between split vertices. Once random loss occurs on split vertices with high importance, results have more distortion.…”

Section: B Simulation Resultsmentioning

confidence: 99%

“…By transmitting part of 3D mesh over TCP and the rest over UDP, they could reduce the distortion caused by packet loss. Cheng et al [7] suggest an analytical model to measure the effect of dependencies among split vertices before streaming. In this method lost data retransmitted.…”

Section: Related Workmentioning

confidence: 99%

“…They only transfer the geometric data, so it can be wrong to always select the closest triangle to insert new vertex. We try to compare the efficiency of our approach with [7], but their decoding time includes data retransmission. Our work focuses more on the prediction scheme and decoding time does not have retransmission delay.…”

Section: Comparison With Priors Workmentioning

confidence: 99%

“…However, these methods may result in an undesired delay due to the data retransmission mechanism. To alleviate the delay, methods utilize hybrid TCP and UDP connections are suggested in [5,6,7]. The use of UDP can lead to packet loss, so methods have been developed to enable packet loss recovery.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

A Comprehensive Approach for Streaming 3D Progressive Meshes

Tang

Guo

Prabhakaran

2009

2009 11th IEEE International Symposium on Multimedia

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Abstract-Fast and efficient streaming of detailed 3D model over lossy network has long been a challenge, although progressive compression techniques were proposed long time ago. One reason is that packet loss occurring in unreliable networks is highly unpredictable, and leads to connectivity inconsistency and distortions. In this paper, we address this problem by proposing a receiver-based loss tolerance scheme based on a prediction technique. Our method works without introducing protection bits and retransmission. We stream mesh refinement data on reliable and unreliable networks separately so as to reduce the transmission delay as well as to obtain a satisfactory decompression result. The tests indicate that the decompression is completed quickly, suggesting that it is a practical solution. Moreover, the proposed prediction technique achieves a good approximation of the original mesh with low distortion.

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Section: B Simulation Resultsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Comparison With Priors Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

A Comprehensive Approach for Streaming 3D Progressive Meshes

Tang

Guo

Prabhakaran

2009

2009 11th IEEE International Symposium on Multimedia

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“…Yan et al [14] and AlRegib et al [1] separately propose different approaches using redundant bits to minimize the distortion caused by packet loss. Cheng et al [3] suggest an analytical model to measure streaming of progressive meshes. Li et al [7] suggest a prediction method to tolerate packet loss.…”

Section: Related Workmentioning

confidence: 99%

Streaming 3D shape deformations in collaborative virtual environment

Tang¹,

Rong²,

Guo³

et al. 2010

2010 IEEE Virtual Reality Conference (VR)

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Collaborative virtual environment has been limited on static or rigid 3D models, due to the difficulties of real-time streaming of large amounts of data that is required to describe motions of 3D deformable models. Streaming shape deformations of complex 3D models arising from a remote user's manipulations is a challenging task. In this paper, we present a framework based on spectral transformation that encodes surface deformations in a frequency format to successfully meet the challenge, and demonstrate its use in a distributed virtual environment. Our research contributions through this framework include: i) we reduce the data size to be streamed for surface deformations since we stream only the transformed spectral coefficients and not the deformed model; ii) we propose a mapping method to allow models with multi-resolutions to have the same deformations simultaneously; iii) our streaming strategy can tolerate loss without the need for special handling of packet loss. Our system guarantees real-time transmission of shape deformations and ensures the smooth motions of 3D models. Moreover, we achieve very effective performance over real Internet conditions as well as a local LAN. Experimental results show that we get low distortion and small delays even when surface deformations of large and complicated 3D models are streamed over lossy networks. KEYWORDS:Collaborative Interaction, Distributed Virtual Reality, 3D Shape Deformation. INDEX TERMS: H.5.1 [Information Interfaces and Presentation]:Multimedia Information Systems -Artificial, augmented, and virtual realities. INTRODUCTIONWith the rapid advances of networks, computer-assisted collaborative virtual environment has been profoundly involved into many aspects of our daily life. Traditional collaborative virtual environments mainly employ video, audio, or text to communicate, and extensive research has helped technologies to transmit these media to remote sites in real-time. Compared with traditional media, 3D models can represent objects in a more realistic and comprehensive manner. Therefore, they have received increasing attentions in collaborative virtual environments. However, the current state-of-the-art technologies cannot facilitate a real-time collaborative virtual environment where large and complicated 3D models and their related shape deformations are involved. Prior researchers have proposed algorithms to effectively transfer large and complex 3D models over network under different conditions, nevertheless these methods focus on static/rigid 3D models only. Some researchers generate 3D models' shape deformations offline, and stream them as animations. But these methods work off-line instead of real-time.Real-time streaming of 3D models' deformable motions faces two grand challenges, namely high computational cost and requirement of transmitting a large amount of data in real-time. For a deformable 3D model, the number of DOFs could be as large as the size of the 3D model. Therefore describing the shape deformations of a 3D deformable mod...

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Streaming 3D deforming surfaces with dynamic resolution control

Zhang

Dou

Zhou

et al. 2013

Computer Animation & Virtual

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Real-time streaming of shape deformations in a shared distributed virtual environment is a challenging task due to the difficulty of transmitting large amounts of 3D animation data to multiple receiving parties at a high frame rate. In this paper, we present a framework for streaming 3D shape deformations, which allows shapes with multi-resolutions to share the same deformations simultaneously in real time. The geometry and motion of deforming mesh or point-sampled surfaces are compactly encoded, transmitted, and reconstructed using the spectra of the manifold harmonics. A receiver-based multiresolution surface reconstruction approach is introduced, which allows deforming shapes to switch smoothly between continuous multi-resolutions. On the basis of this dynamic reconstruction scheme, a frame rate control algorithm is further proposed to achieve rendering at interactive rates. We also demonstrate an efficient interpolation-based strategy to reduce computing of deformation. The experiments conducted on both mesh and point-sampled surfaces show that our approach achieves efficient performance even if deformations of complex 3D surfaces are streamed.

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An analytical model for progressive mesh streaming

Cited by 29 publications

References 16 publications

A Comprehensive Approach for Streaming 3D Progressive Meshes

A Comprehensive Approach for Streaming 3D Progressive Meshes

Streaming 3D shape deformations in collaborative virtual environment

Streaming 3D deforming surfaces with dynamic resolution control

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