added to lit review, fps/latency results
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@online{arcore-unity,
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@online{arcore-unity,
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author = {Google},
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author = {Google},
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date = {2018-02-23},
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date = {2018-02-23},
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organization = {Google},
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title = {ARCore Unity SDK},
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title = {ARCore Unity SDK},
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url = {https://github.com/google-ar/arcore-unity-sdk},
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url = {https://github.com/google-ar/arcore-unity-sdk},
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urldate = {2020-03-27}
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urldate = {2020-03-27}
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@ -452,3 +453,92 @@
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year = {2005}
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year = {2005}
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}
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}
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@article{visual-hull-laurentini,
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author = {Laurentini, Aldo},
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doi = {10.1109/34.273735},
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journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
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journaltitle = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
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month = feb,
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number = {2},
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pages = {150--162},
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title = {The visual hull concept for silhouette-based image understanding},
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url = {https://ieeexplore.ieee.org/abstract/document/273735},
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urldate = {2020-05-06},
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volume = {16},
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year = {1994}
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}
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@inproceedings{cuda-visual-hull,
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abstract = {In this paper we present two efficient GPU-based visual hull computation algorithms. We compare them in terms of performance using image sets of varying size and different voxel resolutions. In addition, we present a real-time 3D reconstruction system which uses the proposed GPU-based reconstruction method to achieve real-time performance (30 fps) using 16 cameras and 4 PCs.},
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author = {{Ladikos}, A. and {Benhimane}, S. and {Navab}, N.},
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booktitle = {2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops},
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doi = {10.1109/CVPRW.2008.4563098},
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isbn = {978-1-4244-2339-2},
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issn = {2160-7508},
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keywords = {computational geometry; image reconstruction; image resolution; visual hull computation; real-time 3D reconstruction; CUDA; GPU; image sets; voxel resolutions; real-time performance; Image reconstruction; Cameras; Real time systems; Reconstruction algorithms; Personal communication networks; Shape; Hardware; Image segmentation; Distributed computing; Computer science},
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month = {June},
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pages = {1--8},
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publisher = {IEEE},
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title = {Efficient visual hull computation for real-time 3D reconstruction using CUDA},
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url = {https://ieeexplore.ieee.org/abstract/document/4563098},
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urldate = {2020-05-06},
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year = {2008}
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}
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@article{microsoft-mixed-reality-studios,
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address = {New York, NY, USA},
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articleno = {69},
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author = {Collet, Alvaro and Chuang, Ming and Sweeney, Pat and Gillett, Don and Evseev, Dennis and Calabrese, David and Hoppe, Hugues and Kirk, Adam and Sullivan, Steve},
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doi = {10.1145/2766945},
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issn = {0730-0301},
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issue_date = {August 2015},
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journal = {ACM Trans. Graph.},
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keywords = {MPEG; multi-view stereo; mesh tracking; 3D video; geometry compression; surface reconstruction},
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month = jul,
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number = {4},
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numpages = {13},
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publisher = {Association for Computing Machinery},
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title = {High-Quality Streamable Free-Viewpoint Video},
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url = {https://opdhsblobprod03.blob.core.windows.net/contents/503db294612a42b3b95420aaabac44cc/4090ebdf84f413793b8cc1a1271a10c5?sv=2018-03-28&sr=b&si=ReadPolicy&sig=WE0q8BmNHfMXk7lk1SvB8KuKBavTZn%2BXHdYzcNRFtDk%3D&st=2020-05-06T12%3A29%3A54Z&se=2020-05-07T12%3A39%3A54Z},
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urldate = {2020-05-06},
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volume = {34},
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year = {2015}
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}
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@inproceedings{hull-correspondences,
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author = {{Ahmed}, N. and {Theobalt}, C. and {Rossl}, C. and {Thrun}, S. and {Seidel}, H.},
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booktitle = {2008 IEEE Conference on Computer Vision and Pattern Recognition},
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doi = {10.1109/CVPR.2008.4587758},
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isbn = {978-1-4244-2242-5},
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issn = {1063-6919},
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month = jun,
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pages = {1--8},
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title = {Dense correspondence finding for parametrization-free animation reconstruction from video},
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url = {https://ieeexplore.ieee.org/abstract/document/4587758},
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urldate = {2020-05-06},
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year = {2008}
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}
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@article{surrey-surface-capture,
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author = {{Starck}, J. and {Hilton}, A.},
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doi = {10.1109/MCG.2007.68},
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journal = {IEEE Computer Graphics and Applications},
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number = {3},
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pages = {21--31},
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title = {Surface Capture for Performance-Based Animation},
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url = {https://ieeexplore.ieee.org/abstract/document/4178157},
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urldate = {2020-05-06},
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volume = {27},
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year = {2007}
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}
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@online{structure-sensor,
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author = {Occipital},
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month = sep,
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organization = {Occipital},
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title = {Structure Sensor},
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url = {https://structure.io/structure-sensor},
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urldate = {2020-05-06},
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year = {2013}
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}
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