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A Visual Latency Estimator for 3D Tele-Immersion

Published: 20 June 2017 Publication History

Abstract

3D Tele-Immersion systems allow geographically distributed users to interact in a virtual world using their "live" 3D models. The capture, reconstruction, transfer, and rendering of these models introduce significant latency into the system. Implicit Latency (ℒ') can be estimated using system clocks to measure the time after the data was received from the RGB-D camera, till the request to render the result. The Observed Latency (ℒ) between a real world event and the event being rendered on the display, cannot be accurately represented by ℒ' since ℒ' ignores the time taken to capture, or update the display, etc. In this paper, a Visual Pattern based Latency Estimation (VPLE) approach is introduced to calculate the real world visual latency of a system without the need for any custom hardware. VPLE generates a constantly changing pattern that is captured and rendered by the 3DTI system. An external observer records both the pattern and the rendered results at high frame rates. ℒ is estimated by calculating the difference between the generated and rendered patterns. VPLE is extended to allow ℒ estimation between geographically distributed sites. Evaluations show that the accuracy of VPLE depends on the refresh rate of the pattern, and is within 4ms. ℒ of a distributed 3DTI system implemented on the GPU is significantly lower than the CPU implementation, and is comparable to video streaming. It is also shown that the ℒ' estimates for GPU based 3DTI implementations are off by almost 100% compared to the ℒ.

References

[1]
Bernard D. Adelstein, Eric R. Johnston, and Stephen R. Ellis. 1996. Dynamic Response of Electromagnetic Spatial Displacement Trackers. Presence: Teleoper. Virtual Environ. 5, 3 (Jan. 1996), 302--318.
[2]
D. Alexiadis, D. Zarpalas, and P. Daras. 2014. Fast and smooth 3D reconstruction using multiple RGB-Depth sensors. In Visual Communications and Image Processing Conference, 2014 IEEE. 173--176.
[3]
S. Beck, A. Kunert, A. Kulik, and B. Froehlich. 2013. Immersive Group-to-Group Telepresence. Visualization and Computer Graphics, IEEE Transactions on 19, 4 (April 2013), 616--625.
[4]
O. Boyaci, A. Forte, S. A. Baset, and H. Schulzrinne. 2009. vDelay: A Tool to Measure Capture-to-Display Latency and Frame Rate. In 2009 11th IEEE International Symposium on Multimedia. 194--200.
[5]
Kuan-Ta Chen, Yu-Chun Chang, Po-Han Tseng, Chun-Ying Huang, and Chin-Laung Lei. 2011. Measuring the Latency of Cloud Gaming Systems. In Proceedings of the 19th ACM International Conference on Multimedia (MM '11). ACM, New York, NY, USA, 1269--1272.
[6]
K. Desai, K. Bahirat, S. Raghuraman, and B. Prabhakaran. 2015. Network Adaptive Textured Mesh Generation for Collaborative 3D Tele-Immersion. In 2015 IEEE International Symposium on Multimedia (ISM). 107--112.
[7]
Massimiliano Di Luca. 2010. New Method to Measure End-to-end Delay of Virtual Reality. Presence: Teleoper. Virtual Environ. 19, 6 (Dec. 2010), 569--584.
[8]
Sebastian Friston and Anthony Steed. 2014. Measuring Latency in Virtual Environments. IEEE Transactions on Visualization and Computer Graphics 20, 4 (April 2014), 616--625.
[9]
Ding He, Ding He Fuhu, Dave Pape, Greg Dawe, and Dan S. 2000. Video-Based Measurement of System Latency. In International Immersive Projection Technology Workshop.
[10]
Jack Jansen. 2014. VideoLat: An Extensible Tool for Multimedia Delay Measurements. In Proceedings of the 22Nd ACM International Conference on Multimedia (MM '14). ACM, New York, NY, USA, 683--686.
[11]
A. Kryczka, A. Arefin, and K. Nahrstedt. 2013. AvCloak: A Tool for Black Box Latency Measurements in Video Conferencing Applications. In 2013 IEEE International Symposium on Multimedia. 271--278.
[12]
Gregorij Kurillo and Ruzena Bajcsy. 2013. 3D teleimmersion for collaboration and interaction of geographically distributed users. Virtual Reality 17, 1 (2013), 29--43.
[13]
R. Mekuria, M. Sanna, E. Izquierdo, D.C.A. Bulterman, and P. Cesar. 2014. Enabling Geometry-Based 3-D Tele-Immersion With Fast Mesh Compression and Linear Rateless Coding. Multimedia, IEEE Transactions on 16, 7 (Nov 2014), 1809--1820.
[14]
Mark R. Mine. 1993. Characterization of End-to-End Delays in Head-Mounted Display Systems. Technical Report. Chapel Hill, NC, USA.
[15]
S. Ohl, M. Willert, and O. Staadt. 2015. Latency in Distributed Acquisition and Rendering for Telepresence Systems. IEEE Transactions on Visualization and Computer Graphics 21, 12 (Dec 2015), 1442--1448.
[16]
N. Otsu. 1979. A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems, Man, and Cybernetics 9, 1 (Jan 1979), 62--66.
[17]
Suraj Raghuraman and Balakrishnan Prabhakaran. 2015. Distortion Score Based Pose Selection for 3D Tele-immersion. In Proceedings of the 21st ACM Symposium on Virtual Reality Software and Technology (VRST '15). ACM, New York, NY, USA, 227--236.
[18]
Tobias Sielhorst, Wu Sa, Ali Khamene, Frank Sauer, and Nassir Navab. 2007. Measurement of Absolute Latency for Video See Through Augmented Reality. In Proceedings of the 2007 6th IEEE and ACM International Symposium on Mixed and Augmented Reality (ISMAR '07). IEEE Computer Society, Washington, DC, USA, 1--4.
[19]
Anthony Steed. 2008. A Simple Method for Estimating the Latency of Interactive, Real-time Graphics Simulations. In Proceedings of the 2008 ACM Symposium on Virtual Reality Software and Technology (VRST '08). ACM, New York, NY, USA, 123--129.
[20]
Colin Swindells, John C. Dill, and Kellogg S. Booth. 2000. System Lag Tests for Augmented and Virtual Environments. In Proceedings of the 13th Annual ACM Symposium on User Interface Software and Technology (UIST '00). ACM, New York, NY, USA, 161--170.
[21]
R. Vasudevan, G. Kurillo, E. Lobaton, T. Bernardin, O. Kreylos, R. Bajcsy, and K. Nahrstedt. 2011. High-Quality Visualization for Geographically Distributed 3-D Teleimmersive Applications. Multimedia, IEEE Transactions on 13, 3 (June 2011), 573--584.
[22]
C. Wei, H. Chen, M. Song, M. T. Sun, and K. Lau. 2013. A capture-to-display delay measurement system for visual communication applications. In 2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference. 1--4.
[23]
W. Wu, A. Arefin, G. Kurillo, P. Agarwal, K. Nahrstedt, and R. Bajcsy. 2011. Color-plus-depth level-of-detail in 3D tele-immersive video: a psychophysical approach. In Proceedings of the 19th ACM international conference on Multimedia (MM '11). ACM, New York, NY, USA, 13--22.
[24]
W. Wu, Y. Dong, and A. Hoover. 2013. Measuring Digital System Latency from Sensing to Actuation at Continuous 1-ms Resolution. Presence 22, 1 (Feb 2013), 20--35.
[25]
Zhong Zhou, Xiuwen Chen, Lin Zhang, and Xuefeng Chang. 2011. Internet-wide multi-party tele-immersion framework for remote 3D collaboration. In VR Innovation (ISVRI), 2011 IEEE International Symposium on. 183--188.

Cited By

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  • (2021)AliceVision MeshroomProceedings of the 12th ACM Multimedia Systems Conference10.1145/3458305.3478443(241-247)Online publication date: 24-Jun-2021
  • (2019)Overcoming latency with motion prediction in directional autostereoscopic displaysJournal of the Society for Information Display10.1002/jsid.84828:3(252-261)Online publication date: 31-Oct-2019

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cover image ACM Conferences
MMSys'17: Proceedings of the 8th ACM on Multimedia Systems Conference
June 2017
407 pages
ISBN:9781450350020
DOI:10.1145/3083187
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 20 June 2017

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Author Tags

  1. 3D Reconstruction
  2. 3D Tele Presence
  3. 3D Tele-immersion
  4. Latency

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MMSys'17
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MMSys'17: Multimedia Systems Conference 2017
June 20 - 23, 2017
Taipei, Taiwan

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MMSys'17 Paper Acceptance Rate 13 of 47 submissions, 28%;
Overall Acceptance Rate 176 of 530 submissions, 33%

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Cited By

View all
  • (2021)AliceVision MeshroomProceedings of the 12th ACM Multimedia Systems Conference10.1145/3458305.3478443(241-247)Online publication date: 24-Jun-2021
  • (2019)Overcoming latency with motion prediction in directional autostereoscopic displaysJournal of the Society for Information Display10.1002/jsid.84828:3(252-261)Online publication date: 31-Oct-2019

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