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Fast Lossless Depth Image Compression

Published: 17 October 2017 Publication History

Abstract

A lossless image compression technique for 16-bit single channel images typical of depth cameras such as Microsoft Kinect is presented. The proposed "RVL" algorithm achieves similar or better compression rates as existing lossless techniques, yet is much faster. Furthermore, the algorithm's implementation can be very simple; a prototype implementation of less than one hundred lines of C is provided. The algorithm's balance of speed and compression make it especially useful in interactive applications of multiple depth cameras on local area networks. RVL is compared to a variety of existing lossless techniques, and demonstrated in a network of eight Kinect v2 cameras.

References

[1]
CharLS, a C++ JPEG-LS library implementation. https://github.com/team-charls/charls.
[2]
Drossaers, M. Data Compression For the Kinect. https://thebytekitchen.com/2014/03/24/data-compression-for-the-kinect/.
[3]
Fu, J., Miao, D., Yu, W., Wang, S., Lu, Y., & Li, S. (2013). Kinect-like depth data compression. IEEE Transactions on Multimedia, 15(6), 1340--1352.
[4]
Gautier, J., Le Meur, O., & Guillemot, C. (2012, May). Efficient depth map compression based on lossless edge coding and diffusion. In Picture Coding Symposium (PCS), 2012 (pp. 81--84).
[5]
Jafarabad, M. Y., Kiani, V., Hamedani, T., & Harati, A. (2014, May). Depth image compression using geometrical wavelets. 6th Conference on Information and Knowledge Technology (IKT), 2014.
[6]
Jones, B., Rajinder Sodhi, R., Murdock, M., Mehra, R., Benko, H., Wilson, A., Ofek, E., MacIntyre, B., Raghuvanshi, N., and Shapira, L. 2014. RoomAlive: magical experiences enabled by scalable, adaptive projector-camera units. In Proc of the 27th annual ACM symposium on User interface software and technology (UIST '14). ACM, New York, NY, USA, 637--644.
[7]
Liu, Y., Beck, S., Wang, R., Li, J., Xu, H., Yao, S., ... & Froehlich, B. (2015, September). Hybrid lossless-lossy compression for real-time depth-sensor streams in 3D telepresence applications. In Pacific Rim Conference on Multimedia (pp. 442--452).
[8]
Mehrotra, S., Zhang, Z., Cai, Q., Zhang, C., & Chou, P. A. (2011, October). Low-complexity, near-lossless coding of depth maps from Kinect-like depth cameras. In Multimedia Signal Processing (MMSP), 2011 IEEE 13th International Workshop on (pp. 1--6).
[9]
Kanika Modi, Prem K. Kalra, and Subodh Kumar. 2014. Compression of Noisy Depth Image using Planes. In Proceedings of the 2014 Indian Conference on Computer Vision Graphics and Image Processing (ICVGIP '14). ACM, New York, NY, USA.
[10]
Lan, C., Xu, J. and Wu, F., 2012, July. Improving depth compression in HEVC by pre/post processing. In Multimedia and Expo Workshops (ICMEW), 2012 IEEE International Conference on (pp. 611--616).
[11]
Pece, F., Kautz, J., Weyrich, T.: Adapting standard video codecs for depth streaming. In: Proceedings of EGVE-JVRC 2011, pp. 59--66, Aire-la-Ville, Switzerland. Eurographics Association (2011)
[12]
RoomAlive Toolkit. https://github.com/Microsoft/RoomAliveToolkit.
[13]
Stuhmer, J., Nowozin, S., Fitzgibbon, A., Szeliski, R., Perry, T., Acharya, S., Cremers, D., and Shotton, J. 2015. Model-Based Tracking at 300Hz using Raw Time-of-Flight Observations. In ICCV, pp. 3577--3585.
[14]
Tomasi, C., and Manduchi, R. (1998). Bilateral filtering for gray and color images. In Sixth International Conference on Computer Vision (pp. 839--846).
[15]
Varadarajan, K. M., Zhou, K., & Vincze, M. (2012, November). RGB and depth intra-frame Cross-Compression for low bandwidth 3D video. In Pattern Recognition (ICPR), 2012 21st International Conference on (pp. 955--958).
[16]
Wobbrock, J. O., Wilson, A., and Li, Y. 2007. Gestures without libraries, toolkits or training: a $1 recognizer for user interface prototypes. In Proc. of the 20th annual ACM symposium on User interface software and technology (UIST '07). 159--168.
[17]
Yuan, Y., Cheung, G., Frossard, P., Le Callet, P., & Zhao, V. H. (2015, October). Contour approximation & depth image coding for virtual view synthesis. In Multimedia Signal Processing (MMSP), 2015 IEEE 17th International Workshop on (pp. 1--6).

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  1. Fast Lossless Depth Image Compression

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    cover image ACM Conferences
    ISS '17: Proceedings of the 2017 ACM International Conference on Interactive Surfaces and Spaces
    October 2017
    504 pages
    ISBN:9781450346917
    DOI:10.1145/3132272
    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 the author(s) 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: 17 October 2017

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    Author Tags

    1. Depth image compression
    2. interactive spaces

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    ISS '17
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    ISS '17: Interactive Surfaces and Spaces
    October 17 - 20, 2017
    Brighton, United Kingdom

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    ISS '17 Paper Acceptance Rate 32 of 119 submissions, 27%;
    Overall Acceptance Rate 147 of 533 submissions, 28%

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    • (2024)Edge-assisted Real-time Dynamic 3D Point Cloud Rendering for Multi-party Mobile Virtual RealityProceedings of the 32nd ACM International Conference on Multimedia10.1145/3664647.3681650(2824-2832)Online publication date: 28-Oct-2024
    • (2024)The Pop-Up Metaverse: A Multi-User, Multi-Tasking Spatial Computing Environment for Collaborative Spatial Problem-Solving.Extended Abstracts of the CHI Conference on Human Factors in Computing Systems10.1145/3613905.3648677(1-5)Online publication date: 11-May-2024
    • (2024)Volumetric Hybrid Workspaces: Interactions with Objects in Remote and Co-located TelepresenceProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642814(1-16)Online publication date: 11-May-2024
    • (2024)Comparing Synchronous and Asynchronous Task Delivery in Mixed Reality EnvironmentsIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.337203430:5(2776-2784)Online publication date: 4-Mar-2024
    • (2023)Lifting-based lossless image coding using cellular neural network predictors and context estimators optimized by adaptive differential evolutionNonlinear Theory and Its Applications, IEICE10.1587/nolta.14.60914:3(609-627)Online publication date: 2023
    • (2023)Neural Network Assisted Depth Map Packing for Compression Using Standard Hardware Video CodecsACM Transactions on Multimedia Computing, Communications, and Applications10.1145/358844019:5s(1-20)Online publication date: 7-Jun-2023
    • (2023)CollabVr: Reprojection-Based Edge-Client Collaborative Rendering for Real-Time High-Quality Mobile Virtual Reality2023 IEEE Real-Time Systems Symposium (RTSS)10.1109/RTSS59052.2023.00034(304-316)Online publication date: 5-Dec-2023
    • (2022)Remote Training for Medical Staff in Low-Resource Environments Using Augmented RealityJournal of Imaging10.3390/jimaging81203198:12(319)Online publication date: 29-Nov-2022
    • (2022)InDepthProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35172606:1(1-25)Online publication date: 29-Mar-2022
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