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@article{dong2013plenoptic,
	Author = {Dong, Fengchun and Ieng, Sio-Hoi and Savatier, Xavier and Etienne-Cummings, Ralph and Benosman, Ryad},
	Date-Added = {2020-05-24 15:25:50 +1000},
	Date-Modified = {2020-05-24 15:25:50 +1000},
	Journal = ijrr,
	Number = {2},
	Pages = {206--217},
	Publisher = {SAGE Publications},
	Title = {Plenoptic cameras in real-time robotics},
	Volume = {32},
	Year = {2013}}

@article{wadhwa2018portraitmode,
	Archiveprefix = {arXiv},
	Author = {Neal Wadhwa and Rahul Garg and David E. Jacobs and Bryan E. Feldman and Nori Kanazawa and Robert Carroll and Yair Movshovitz{-}Attias and Jonathan T. Barron and Yael Pritch and Marc Levoy},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/journals/corr/abs-1806-04171.bib},
	Date-Added = {2020-05-17 20:50:42 +1000},
	Date-Modified = {2020-05-17 20:50:52 +1000},
	Eprint = {1806.04171},
	Journal = {CoRR},
	Timestamp = {Mon, 13 Aug 2018 16:48:00 +0200},
	Title = {Synthetic Depth-of-Field with a Single-Camera Mobile Phone},
	Url = {http://arxiv.org/abs/1806.04171},
	Volume = {abs/1806.04171},
	Year = {2018},
	Bdsk-Url-1 = {http://arxiv.org/abs/1806.04171}}

@article{levoy2019lowlight,
	Author = {Liba, Orly and Murthy, Kiran and Tsai, Yun-Ta and Brooks, Tim and Xue, Tianfan and Karnad, Nikhil and He, Qiurui and Barron, Jonathan T. and Sharlet, Dillon and Geiss, Ryan and et al.},
	Date-Added = {2020-05-17 20:48:25 +1000},
	Date-Modified = {2020-05-17 20:48:35 +1000},
	Doi = {10.1145/3355089.3356508},
	Issn = {1557-7368},
	Journal = {ACM Transactions on Graphics},
	Month = {Nov},
	Number = {6},
	Pages = {1--16},
	Publisher = {Association for Computing Machinery (ACM)},
	Title = {Handheld mobile photography in very low light},
	Url = {http://dx.doi.org/10.1145/3355089.3356508},
	Volume = {38},
	Year = {2019},
	Bdsk-Url-1 = {http://dx.doi.org/10.1145/3355089.3356508}}

@inproceedings{faluvegi2019threedcnn,
	Author = {{\'A}. {Faluv{\'e}gi} and Q. {Bolse{\'e}} and S. {Nedevschi} and V. {D{\u a}d{\^a}rlat} and A. {Munteanu}},
	Booktitle = {2019 International Conference on {3D} Immersion (IC3D)},
	Date-Added = {2020-05-16 18:22:59 +1000},
	Date-Modified = {2020-05-24 15:41:14 +1000},
	Pages = {1-5},
	Title = {A {3D} Convolutional Neural Network for Light Field Depth Estimation},
	Year = {2019}}

@article{shin2018epinet,
	Author = {Shin, Changha and Jeon, Hae-Gon and Yoon, Youngjin and Kweon, Inso and Kim, Seon},
	Date-Added = {2020-05-16 18:12:32 +1000},
	Date-Modified = {2020-05-16 18:12:36 +1000},
	Month = {04},
	Title = {EPINET: A Fully-Convolutional Neural Network Using Epipolar Geometry for Depth from Light Field Images},
	Year = {2018}}

@inproceedings{heber2017shape,
	Author = {S. {Heber} and T. {Pock}},
	Booktitle = {2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	Date-Added = {2020-05-16 18:04:32 +1000},
	Date-Modified = {2020-05-16 18:04:32 +1000},
	Pages = {3746-3754},
	Title = {Convolutional Networks for Shape from Light Field},
	Year = {2016}}

@article{leistner2019lfdepthcnn,
	Author = {Leistner, Titus and Schilling, Hendrik and Mackowiak, Radek and Gumhold, Stefan and Rother, Carsten},
	Date-Added = {2020-05-16 17:52:37 +1000},
	Date-Modified = {2020-05-16 17:52:52 +1000},
	Doi = {10.1109/3dv.2019.00036},
	Isbn = {9781728131313},
	Journal = {2019 International Conference on 3D Vision (3DV)},
	Month = {Sep},
	Publisher = {IEEE},
	Title = {Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift},
	Url = {http://dx.doi.org/10.1109/3DV.2019.00036},
	Year = {2019},
	Bdsk-Url-1 = {http://dx.doi.org/10.1109/3DV.2019.00036},
	Bdsk-Url-2 = {http://dx.doi.org/10.1109/3dv.2019.00036}}

@book{pybullet2017,
	Author = {Erwin Coumans and Yunfei Bai},
	Date-Added = {2020-04-11 08:56:33 +1000},
	Date-Modified = {2020-05-24 15:41:47 +1000},
	Title = {Pybullet, a Python module for physics simulation in robotics, games and machine learning},
	Year = {2017}}

@book{gothe2009perspective,
	Author = {Gothe, Wolfram},
	Date-Added = {2020-04-10 15:26:30 +1000},
	Date-Modified = {2020-04-10 15:26:38 +1000},
	Month = {Jul},
	Title = {Three-point perspective projection.},
	Year = {2009}}

@book{behrendt2006isometric,
	Author = {Behrendt, Stefan},
	Date-Added = {2020-04-10 15:26:30 +1000},
	Date-Modified = {2020-04-10 15:26:38 +1000},
	Month = {Aug},
	Title = {Isometric projection.},
	Year = {2006}}

@article{jiao2018magicvo,
	Archiveprefix = {arXiv},
	Author = {Jian Jiao and Jichao Jiao and Yaokai Mo and Weilun Liu and Zhongliang Deng},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/journals/corr/abs-1811-10964.bib},
	Date-Added = {2020-03-16 10:26:02 +1100},
	Date-Modified = {2020-03-16 10:26:08 +1100},
	Eprint = {1811.10964},
	Journal = {CoRR},
	Timestamp = {Fri, 30 Nov 2018 12:44:28 +0100},
	Title = {MagicVO: End-to-End Monocular Visual Odometry through Deep Bi-directional Recurrent Convolutional Neural Network},
	Url = {http://arxiv.org/abs/1811.10964},
	Volume = {abs/1811.10964},
	Year = {2018},
	Bdsk-Url-1 = {http://arxiv.org/abs/1811.10964}}

@article{wang2017deepvo,
	Archiveprefix = {arXiv},
	Author = {Sen Wang and Ronald Clark and Hongkai Wen and Niki Trigoni},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/journals/corr/abs-1709-08429.bib},
	Date-Added = {2020-03-16 10:24:15 +1100},
	Date-Modified = {2020-04-10 17:04:20 +1000},
	Eprint = {1709.08429},
	Journal = {CoRR},
	Timestamp = {Mon, 11 Mar 2019 07:46:34 +0100},
	Title = {Deep{VO}: Towards End-to-End Visual Odometry with Deep Recurrent Convolutional Neural Networks},
	Url = {http://arxiv.org/abs/1709.08429},
	Volume = {abs/1709.08429},
	Year = {2017},
	Bdsk-Url-1 = {http://arxiv.org/abs/1709.08429}}

@inproceedings{dataset-cityscapes,
	Author = {Cordts, Marius and Omran, Mohamed and Ramos, Sebastian and Rehfeld, Timo and Enzweiler, Markus and Benenson, Rodrigo and Franke, Uwe and Roth, Stefan and Schiele, Bernt},
	Booktitle = {Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
	Date-Added = {2020-03-16 10:01:43 +1100},
	Date-Modified = {2020-03-16 10:01:51 +1100},
	Title = {The Cityscapes Dataset for Semantic Urban Scene Understanding},
	Year = {2016}}

@misc{zhang1994icp,
	Author = {Zhengyou Zhang},
	Date-Added = {2020-03-08 15:42:46 +1100},
	Date-Modified = {2020-03-08 15:42:52 +1100},
	Title = {Iterative point matching for registration of free-form curves and surfaces},
	Year = {1994}}

@article{besl1992icp,
	Author = {P. J. {Besl} and N. D. {McKay}},
	Date-Added = {2020-03-08 15:41:02 +1100},
	Date-Modified = {2020-05-27 08:45:10 +1000},
	Doi = {10.1109/34.121791},
	Issn = {1939-3539},
	Journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
	Keywords = {computational geometry;convergence of numerical methods;iterative methods;optimisation;pattern recognition;picture processing;3D shape registration;pattern recognition;point set registration;iterative closest point;geometric entity;mean-square distance metric;convergence;geometric model;Solid modeling;Motion estimation;Iterative closest point algorithm;Iterative algorithms;Testing;Inspection;Shape measurement;Iterative methods;Convergence;Quaternions},
	Month = {Feb},
	Number = {2},
	Pages = {239-256},
	Title = {A method for registration of {3D} shapes},
	Volume = {14},
	Year = {1992},
	Bdsk-Url-1 = {https://doi.org/10.1109/34.121791}}

@article{medioni1992icp,
	Abstract = {We study the problem of creating a complete model of a physical object. Although this may be possible using intensity images, we here use images which directly provide access to three dimensional information. The first problem that we need to solve is to find the transformation between the different views. Previous approaches either assume this transformation to be known (which is extremely difficult for a complete model), or compute it with feature matching (which is not accurate enough for integration). In this paper, we propose a new approach which works on range data directly and registers successive views with enough overlapping area to get an accurate transformation between views. This is performed by minimizing a functional which does not require point-to-point matches. We give the details of the registration method and modelling procedure and illustrate them on real range images of complex objects.},
	Author = {Yang Chen and G{\'e}rard Medioni},
	Date-Added = {2020-03-08 15:40:08 +1100},
	Date-Modified = {2020-03-08 15:40:19 +1100},
	Doi = {https://doi.org/10.1016/0262-8856(92)90066-C},
	Issn = {0262-8856},
	Journal = {Image and Vision Computing},
	Keywords = {object modelling, 3D surface registration, range image registration},
	Note = {Range Image Understanding},
	Number = {3},
	Pages = {145 - 155},
	Title = {Object modelling by registration of multiple range images},
	Url = {http://www.sciencedirect.com/science/article/pii/026288569290066C},
	Volume = {10},
	Year = {1992},
	Bdsk-Url-1 = {http://www.sciencedirect.com/science/article/pii/026288569290066C},
	Bdsk-Url-2 = {https://doi.org/10.1016/0262-8856(92)90066-C}}

@article{arun1987svd,
	Address = {USA},
	Author = {Arun, K. S. and Huang, T. S. and Blostein, S. D.},
	Date-Added = {2020-03-08 15:33:01 +1100},
	Date-Modified = {2020-05-27 08:45:33 +1000},
	Doi = {10.1109/TPAMI.1987.4767965},
	Issn = {0162-8828},
	Issue_Date = {May 1987},
	Journal = {IEEE Trans. Pattern Anal. Mach. Intell.},
	Keywords = {least-squares, singular value decomposition, Computer vision, motion estimation, quaternion},
	Month = may,
	Number = {5},
	Numpages = {3},
	Pages = {698--700},
	Publisher = {IEEE Computer Society},
	Title = {Least-Squares Fitting of Two {3D} Point Sets},
	Url = {https://doi.org/10.1109/TPAMI.1987.4767965},
	Volume = {9},
	Year = {1987},
	Bdsk-Url-1 = {https://doi.org/10.1109/TPAMI.1987.4767965}}

@article{horn1987absorientation,
	Author = {Horn, Berthold},
	Date-Added = {2020-03-08 15:30:00 +1100},
	Date-Modified = {2020-03-08 15:30:09 +1100},
	Doi = {10.1364/JOSAA.4.000629},
	Journal = {Journal of the Optical Society A},
	Month = {04},
	Pages = {629-642},
	Title = {Closed-Form Solution of Absolute Orientation Using Unit Quaternions},
	Volume = {4},
	Year = {1987},
	Bdsk-Url-1 = {https://doi.org/10.1364/JOSAA.4.000629}}

@inproceedings{harris1988corners,
	Author = {Chris Harris and Mike Stephens},
	Booktitle = {In Proc. of Fourth Alvey Vision Conference},
	Date-Added = {2020-03-08 14:38:25 +1100},
	Date-Modified = {2020-03-08 14:38:49 +1100},
	Pages = {147--151},
	Title = {A combined corner and edge detector},
	Year = {1988}}

@article{bolles1981ransac,
	Address = {New York, NY, USA},
	Author = {Fischler, Martin A. and Bolles, Robert C.},
	Date-Added = {2020-03-08 12:18:54 +1100},
	Date-Modified = {2020-03-08 12:19:02 +1100},
	Doi = {10.1145/358669.358692},
	Issn = {0001-0782},
	Issue_Date = {June 1981},
	Journal = {Commun. ACM},
	Keywords = {automated cartography, location determination, camera calibration, model fitting, image matching, scene analysis},
	Month = jun,
	Number = {6},
	Numpages = {15},
	Pages = {381--395},
	Publisher = {Association for Computing Machinery},
	Title = {Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography},
	Url = {https://doi.org/10.1145/358669.358692},
	Volume = {24},
	Year = {1981},
	Bdsk-Url-1 = {https://doi.org/10.1145/358669.358692}}

@inbook{longues-higgens1987reconstruction,
	Address = {San Francisco, CA, USA},
	Author = {Longuet-Higgins, H. C.},
	Booktitle = {Readings in Computer Vision: Issues, Problems, Principles, and Paradigms},
	Date-Added = {2020-03-08 12:14:30 +1100},
	Date-Modified = {2020-03-08 12:14:49 +1100},
	Isbn = {0934613338},
	Numpages = {2},
	Pages = {61--62},
	Publisher = {Morgan Kaufmann Publishers Inc.},
	Title = {A Computer Algorithm for Reconstructing a Scene from Two Projections},
	Year = {1987}}

@phdthesis{proenca2018rgbd,
	Author = {Pedro F. Proen{\c c}a},
	Date-Added = {2020-03-02 11:17:15 +1100},
	Date-Modified = {2020-03-02 11:18:12 +1100},
	School = {University of Surrey},
	Title = {Robust RGB-D Odometry under Depth Uncertainty for Structured Environments},
	Year = {2018}}

@article{cadena2016slam,
	Archiveprefix = {arXiv},
	Author = {Cesar Cadena and Luca Carlone and Henry Carrillo and Yasir Latif and Davide Scaramuzza and Jos{\'{e}} Neira and Ian D. Reid and John J. Leonard},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/journals/corr/CadenaCCLSN0L16.bib},
	Date-Added = {2020-03-02 10:43:38 +1100},
	Date-Modified = {2020-03-02 10:44:28 +1100},
	Eprint = {1606.05830},
	Journal = {The Computing Research Repository},
	Timestamp = {Mon, 13 Aug 2018 16:47:35 +0200},
	Title = {Simultaneous Localization And Mapping: Present, Future, and the Robust-Perception Age},
	Url = {http://arxiv.org/abs/1606.05830},
	Year = {2016},
	Bdsk-Url-1 = {http://arxiv.org/abs/1606.05830}}

@book{szeliski2010computervision,
	Address = {Berlin, Heidelberg},
	Author = {Szeliski, Richard},
	Date-Added = {2019-12-01 23:54:04 +1100},
	Date-Modified = {2019-12-01 23:54:13 +1100},
	Edition = {1st},
	Isbn = {1848829345, 9781848829343},
	Publisher = {Springer-Verlag},
	Title = {Computer Vision: Algorithms and Applications},
	Year = {2010}}

@article{mayer2015dispnet,
	Archiveprefix = {arXiv},
	Author = {Nikolaus Mayer and Eddy Ilg and Philip H{\"{a}}usser and Philipp Fischer and Daniel Cremers and Alexey Dosovitskiy and Thomas Brox},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/bib/journals/corr/MayerIHFCDB15},
	Date-Added = {2019-12-01 14:16:24 +1100},
	Date-Modified = {2019-12-01 14:16:30 +1100},
	Eprint = {1512.02134},
	Journal = {The Computing Research Repository},
	Timestamp = {Mon, 13 Aug 2018 16:47:32 +0200},
	Title = {A Large Dataset to Train Convolutional Networks for Disparity, Optical Flow, and Scene Flow Estimation},
	Url = {http://arxiv.org/abs/1512.02134},
	Volume = {abs/1512.02134},
	Year = {2015},
	Bdsk-Url-1 = {http://arxiv.org/abs/1512.02134}}

@article{dansereau2015volumetric,
	Author = {Dansereau, Donald and Pizarro, Oscar and Williams, Stefan},
	Date-Added = {2019-11-28 11:42:56 +1100},
	Date-Modified = {2019-11-28 11:43:05 +1100},
	Doi = {10.1145/2665074},
	Journal = {ACM Transactions on Graphics},
	Month = {03},
	Pages = {1-20},
	Title = {Linear Volumetric Focus for Light Field Cameras},
	Volume = {34},
	Year = {2015},
	Bdsk-Url-1 = {https://doi.org/10.1145/2665074}}

@inproceedings{skinner2016underwaterplenoptic,
	Author = {K. A. {Skinner} and M. {Johnson-Roberson}},
	Booktitle = {2016 International Conference on Intelligent Robots and Systems},
	Date-Added = {2019-11-28 11:37:37 +1100},
	Date-Modified = {2019-11-28 11:37:52 +1100},
	Doi = {10.1109/IROS.2016.7759317},
	Issn = {2153-0866},
	Keywords = {autonomous underwater vehicles;cameras;control engineering computing;graphics processing units;image colour analysis;image reconstruction;robot vision;sensors;solid modelling;real-time underwater 3D reconstruction;plenoptic cameras;terrestrial robotics applications;real-time depth sensors;terrestrial mapping;RGB-D data underwater;graphics processing unit;GPU;3D model;computer vision;AUV;ROV;Cameras;Three-dimensional displays;Lenses;Real-time systems;Sensors;Solid modeling;Image color analysis;plenoptic cameras;light field cameras;underwater 3D reconstruction;real-time 3D reconstruction;computer vision},
	Month = {Oct},
	Pages = {2014-2021},
	Title = {Towards real-time underwater {3D} reconstruction with plenoptic cameras},
	Year = {2016},
	Bdsk-Url-1 = {https://doi.org/10.1109/IROS.2016.7759317}}

@inproceedings{kuehefuss2016rgbdslam,
	Author = {Kuehefuss, Andreas and Zeller, Niclas and Quint, Franz and Stilla, Uwe},
	Date-Added = {2019-11-28 11:35:14 +1100},
	Date-Modified = {2019-11-28 11:35:38 +1100},
	Title = {Feature Based RGB-D SLAM for a Plenoptic Camera},
	Year = {2016}}

@article{dong2013plenopticflow,
	Abstract = { Real-time vision-based navigation is a difficult task largely due to the limited optical properties of single cameras that are usually mounted on robots. Multiple camera systems such as polydioptric sensors provide more efficient and precise solutions for autonomous navigation. They are particularly suitable for motion estimation because they allow one to formulate a linear optimization. These sensors capture the visual information in a more complete form called the plenoptic function that encodes the spatial and temporal light radiance of the scene. The polydioptric sensors are rarely used in robotics because they are usually thought to increase the amount of data produced and require more computational power. This paper shows that these cameras provide more accurate estimation results in mobile robotics navigation if designed properly. It also shows that a plenoptic vision sensor with a resolution ranging from 3 × 3 to 40 × 30 pixels camera, provides higher accuracy than a mono-SLAM running on a 320 × 240 pixels camera. The paper also gives a complete scheme to design usable real-time plenoptic cameras for mobile robotics applications by establishing the link between velocity, resolution and motion estimation accuracy. Finally, experiments on a mobile robot are shown allowing for a comparison between optimal plenoptic visual sensors and single high-resolution cameras. The estimation with the plenoptic sensor is more accurate than a monocular high-definition camera with a processing time 100 times lower. },
	Author = {Fengchun Dong and Sio-Hoi Ieng and Xavier Savatier and Ralph Etienne-Cummings and Ryad Benosman},
	Date-Added = {2019-11-07 12:51:05 +1100},
	Date-Modified = {2019-11-07 12:51:16 +1100},
	Doi = {10.1177/0278364912469420},
	Eprint = {https://doi.org/10.1177/0278364912469420},
	Journal = {The International Journal of Robotics Research},
	Number = {2},
	Pages = {206-217},
	Title = {Plenoptic cameras in real-time robotics},
	Url = {https://doi.org/10.1177/0278364912469420},
	Volume = {32},
	Year = {2013},
	Bdsk-Url-1 = {https://doi.org/10.1177/0278364912469420}}

@article{wang2016lfcnn,
	Archiveprefix = {arXiv},
	Author = {Ting{-}Chun Wang and Jun{-}Yan Zhu and Hiroaki Ebi and Manmohan Chandraker and Alexei A. Efros and Ravi Ramamoorthi},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/bib/journals/corr/WangZECER16},
	Date-Added = {2019-11-06 17:29:38 +1100},
	Date-Modified = {2019-11-06 17:31:26 +1100},
	Eprint = {1608.06985},
	Journal = {The Computing Research Repository},
	Timestamp = {Mon, 13 Aug 2018 16:48:53 +0200},
	Title = {A {4D} Light-Field Dataset and {CNN} Architectures for Material Recognition},
	Url = {http://arxiv.org/abs/1608.06985},
	Year = {2016},
	Bdsk-Url-1 = {http://arxiv.org/abs/1608.06985}}

@inproceedings{sun2016lfdepthcnn,
	Author = {{Xing Sun} and Z. {Xu} and {Nan Meng} and E. Y. {Lam} and H. K. -. {So}},
	Booktitle = {2016 International Joint Conference on Neural Networks (IJCNN)},
	Date-Added = {2019-11-06 17:17:23 +1100},
	Date-Modified = {2019-11-06 17:17:36 +1100},
	Doi = {10.1109/IJCNN.2016.7727222},
	Keywords = {feature extraction;image coding;image recognition;neural net architecture;data-driven light field depth estimation;deep convolutional neural networks;object depth estimation;epipolar-plane images;depth map;enhanced EPI feature extraction;depth information encoding;scene disparity map recognition;CNN architecture;Heidelberg Col-laboratory for image processing benchmark dataset;forward propagation step;Data mining;Human computer interaction;Transforms},
	Pages = {367-374},
	Title = {Data-driven light field depth estimation using deep Convolutional Neural Networks},
	Year = {2016},
	Bdsk-Url-1 = {https://doi.org/10.1109/IJCNN.2016.7727222}}

@inproceedings{neumann2002polydioptric,
	Abstract = {We examine the influence of camera design on the estimation of the motion and structure of a scene from video data. Every camera captures a subset of the light rays passing though some volume in space. By relating the differential structure of the time varying space of light rays to different known and new camera designs, we can establish a hierarchy of cameras. This hierarchy is based upon the stability and complexity of the computations necessary to estimate structure and motion. At the low end of this hierarchy is the standard planar pinhole camera for which the structure from motion problem is non-linear and ill-posed. At the high end is a camera, which we call the full field of view polydioptric camera, for which the problem is linear and stable. We develop design suggestions for the polydioptric camera, and based upon this new design we propose a linear algorithm for structure-from-motion estimation, which combines differential motion estimation with differential stereo.},
	Address = {Berlin, Heidelberg},
	Author = {Neumann, Jan and Ferm{\"u}ller, Cornelia and Aloimonos, Yiannis},
	Booktitle = {Pattern Recognition},
	Date-Added = {2019-11-06 17:12:33 +1100},
	Date-Modified = {2019-11-06 17:12:46 +1100},
	Editor = {Van Gool, Luc},
	Isbn = {978-3-540-45783-1},
	Pages = {618--625},
	Publisher = {Springer Berlin Heidelberg},
	Title = {Polydioptric Cameras: New Eyes for Structure from Motion},
	Year = {2002}}

@inproceedings{dansereau2011plenopticflow,
	Author = {Donald {Dansereau} and Ian {Mahon} and Oscar {Pizarro} and Stephan B. {Williams}},
	Booktitle = {2011 IEEE/RSJ International Conference on Intelligent Robots and Systems},
	Date-Added = {2019-11-06 11:26:02 +1100},
	Date-Modified = {2019-11-06 11:26:23 +1100},
	Doi = {10.1109/IROS.2011.6095080},
	Keywords = {Cameras;Equations;Visualization;Optical sensors;Closed-form solutions;Three dimensional displays;Estimation},
	Pages = {4455-4462},
	Title = {Plenoptic flow: Closed-form visual odometry for light field cameras},
	Year = {2011},
	Bdsk-Url-1 = {https://doi.org/10.1109/IROS.2011.6095080}}

@article{godard2018selfsupervised,
	Archiveprefix = {arXiv},
	Author = {Cl{\'{e}}ment Godard and Oisin {Mac Aodha} and Gabriel J. Brostow},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/bib/journals/corr/abs-1806-01260},
	Date-Added = {2019-11-06 10:23:54 +1100},
	Date-Modified = {2019-11-06 10:24:02 +1100},
	Eprint = {1806.01260},
	Journal = {The Computing Research Repository},
	Timestamp = {Mon, 13 Aug 2018 16:48:01 +0200},
	Title = {Digging Into Self-Supervised Monocular Depth Estimation},
	Url = {http://arxiv.org/abs/1806.01260},
	Year = {2018},
	Bdsk-Url-1 = {http://arxiv.org/abs/1806.01260}}

@article{zhan2018deepfeature,
	Archiveprefix = {arXiv},
	Author = {Huangying Zhan and Ravi Garg and Chamara Saroj Weerasekera and Kejie Li and Harsh Agarwal and Ian D. Reid},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/bib/journals/corr/abs-1803-03893},
	Date-Added = {2019-11-06 10:21:41 +1100},
	Date-Modified = {2019-11-06 10:21:48 +1100},
	Eprint = {1803.03893},
	Journal = {The Computing Research Repository},
	Timestamp = {Mon, 13 Aug 2018 16:47:21 +0200},
	Title = {Unsupervised Learning of Monocular Depth Estimation and Visual Odometry with Deep Feature Reconstruction},
	Url = {http://arxiv.org/abs/1803.03893},
	Year = {2018},
	Bdsk-Url-1 = {http://arxiv.org/abs/1803.03893}}

@article{lowe2004sift,
	Acmid = {996342},
	Address = {Norwell, MA, USA},
	Author = {Lowe, David G.},
	Date-Added = {2019-11-05 14:50:12 +1100},
	Date-Modified = {2019-11-05 14:50:17 +1100},
	Doi = {10.1023/B:VISI.0000029664.99615.94},
	Issn = {0920-5691},
	Issue_Date = {November 2004},
	Journal = {International Journal of Computer Vision},
	Keywords = {image matching, invariant features, object recognition, scale invariance},
	Number = {2},
	Numpages = {20},
	Pages = {91--110},
	Publisher = {Kluwer Academic Publishers},
	Title = {Distinctive Image Features from Scale-Invariant Keypoints},
	Url = {https://doi.org/10.1023/B:VISI.0000029664.99615.94},
	Volume = {60},
	Year = {2004},
	Bdsk-Url-1 = {https://doi.org/10.1023/B:VISI.0000029664.99615.94}}

@article{bay2008surf,
	Acmid = {1370556},
	Address = {New York, NY, USA},
	Author = {Bay, Herbert and Ess, Andreas and Tuytelaars, Tinne and Van Gool, Luc},
	Date-Added = {2019-11-05 14:48:58 +1100},
	Date-Modified = {2019-11-05 14:49:11 +1100},
	Doi = {10.1016/j.cviu.2007.09.014},
	Issn = {1077-3142},
	Issue_Date = {June, 2008},
	Journal = {Computer Vision and Image Understanding},
	Keywords = {Camera calibration, Feature description, Interest points, Local features, Object recognition},
	Number = {3},
	Numpages = {14},
	Pages = {346--359},
	Publisher = {Elsevier Science Inc.},
	Title = {Speeded-Up Robust Features (SURF)},
	Url = {http://dx.doi.org/10.1016/j.cviu.2007.09.014},
	Volume = {110},
	Year = {2008},
	Bdsk-Url-1 = {http://dx.doi.org/10.1016/j.cviu.2007.09.014}}

@article{long2014fcn,
	Archiveprefix = {arXiv},
	Author = {Jonathan Long and Evan Shelhamer and Trevor Darrell},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/bib/journals/corr/LongSD14},
	Date-Added = {2019-11-03 13:03:37 +1100},
	Date-Modified = {2019-11-03 13:03:54 +1100},
	Eprint = {1411.4038},
	Journal = {The Computing Research Repository},
	Timestamp = {Mon, 13 Aug 2018 16:48:17 +0200},
	Title = {Fully Convolutional Networks for Semantic Segmentation},
	Url = {http://arxiv.org/abs/1411.4038},
	Year = {2014},
	Bdsk-Url-1 = {http://arxiv.org/abs/1411.4038}}

@inproceedings{lecun1989cnn,
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	Booktitle = {Proceedings of the IEEE},
	Date-Added = {2019-11-03 13:00:42 +1100},
	Date-Modified = {2019-11-03 13:01:02 +1100},
	Pages = {2278--2324},
	Title = {Gradient-based learning applied to document recognition},
	Year = {1998}}

@article{rumelhart1986backprop,
	Abstract = {We describe a new learning procedure, back-propagation, for networks of neurone-like units. The procedure repeatedly adjusts the weights of the connections in the network so as to minimize a measure of the difference between the actual output vector of the net and the desired output vector. As a result of the weight adjustments, internal `hidden'units which are not part of the input or output come to represent important features of the task domain, and the regularities in the task are captured by the interactions of these units. The ability to create useful new features distinguishes back-propagation from earlier, simpler methods such as the perceptron-convergence procedure1.},
	Author = {Rumelhart, David E. and Hinton, Geoffrey E. and Williams, Ronald J.},
	Da = {1986/10/01},
	Date-Added = {2019-11-02 21:24:30 +1100},
	Date-Modified = {2019-11-02 21:24:40 +1100},
	Doi = {10.1038/323533a0},
	Id = {Rumelhart1986},
	Isbn = {1476-4687},
	Journal = {Nature},
	Number = {6088},
	Pages = {533--536},
	Title = {Learning representations by back-propagating errors},
	Ty = {JOUR},
	Url = {https://doi.org/10.1038/323533a0},
	Volume = {323},
	Year = {1986},
	Bdsk-Url-1 = {https://doi.org/10.1038/323533a0}}

@book{minsky1969perceptrons,
	Added-At = {2008-05-16T13:57:01.000+0200},
	Address = {Cambridge, MA, USA},
	Author = {Minsky, Marvin and Papert, Seymour},
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	Date-Added = {2019-11-02 21:16:25 +1100},
	Date-Modified = {2019-11-02 21:16:37 +1100},
	Description = {: mf : blob : » bibtex},
	Interhash = {d80d4948a422623047f1b800272c0389},
	Intrahash = {06a5a6751b3e61408455fca2ed8d87fc},
	Keywords = {linear-classification neural-networks seminal},
	Publisher = {MIT Press},
	Timestamp = {2008-05-16T13:57:02.000+0200},
	Title = {Perceptrons: An Introduction to Computational Geometry},
	Year = 1969}

@book{nielson2015neuralnets,
	Date-Added = {2019-11-02 21:02:28 +1100},
	Date-Modified = {2019-11-02 21:02:57 +1100},
	Publisher = {Determination Press},
	Title = {Neural Networks and Deep Learning},
	Year = {2015}}

@book{rosenblatt1959neurodynamics,
	Added-At = {2009-10-23T10:49:34.000+0200},
	Author = {Rosenblatt, Frank},
	Biburl = {https://www.bibsonomy.org/bibtex/2804997710831973537a852b3aec6e6c5/gerhard.wohlgenannt},
	Date-Added = {2019-11-02 20:59:45 +1100},
	Date-Modified = {2019-11-02 21:17:36 +1100},
	Description = {phd thesis version 2009-10-23},
	Interhash = {b8e4d1d1f5cdf4b0eead0d95ea274cd5},
	Intrahash = {804997710831973537a852b3aec6e6c5},
	Keywords = {imported},
	Publisher = {Spartan Books},
	Timestamp = {2009-10-23T10:49:38.000+0200},
	Title = {Principles of Neurodynamics},
	Year = 1959}

@incollection{krizhevsky2012alexnet,
	Author = {Alex Krizhevsky and Sutskever, Ilya and Hinton, Geoffrey E},
	Booktitle = {Advances in Neural Information Processing Systems 25},
	Date-Added = {2019-11-02 20:51:54 +1100},
	Date-Modified = {2019-11-02 20:52:16 +1100},
	Editor = {F. Pereira and C. J. C. Burges and L. Bottou and K. Q. Weinberger},
	Pages = {1097--1105},
	Publisher = {Curran Associates, Inc.},
	Title = {ImageNet Classification with Deep Convolutional Neural Networks},
	Url = {http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf},
	Year = {2012},
	Bdsk-Url-1 = {http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf}}

@article{ilsvrc,
	Author = {Olga Russakovsky and Jia Deng and Hao Su and Jonathan Krause and Sanjeev Satheesh and Sean Ma and Zhiheng Huang and Andrej Karpathy and Aditya Khosla and Michael Bernstein and Alexander C. Berg and Li Fei-Fei},
	Date-Added = {2019-11-02 20:44:23 +1100},
	Date-Modified = {2019-11-02 20:44:29 +1100},
	Doi = {10.1007/s11263-015-0816-y},
	Journal = {International Journal of Computer Vision},
	Number = {3},
	Pages = {211-252},
	Title = {{ImageNet Large Scale Visual Recognition Challenge}},
	Volume = {115},
	Year = {2015},
	Bdsk-File-1 = {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},
	Bdsk-Url-1 = {https://doi.org/10.1007/s11263-015-0816-y}}

@article{papert1966vision,
	Author = {Papert, Seymour},
	Date-Added = {2019-11-02 20:32:19 +1100},
	Date-Modified = {2019-11-02 20:32:51 +1100},
	Title = {The Summer Vision Project},
	Year = {1966}}

@article{garg2016unsupervised,
	Archiveprefix = {arXiv},
	Author = {Ravi Garg and Vijay Kumar B. G and Ian D. Reid},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/bib/journals/corr/GargBR16},
	Date-Added = {2019-11-02 19:39:22 +1100},
	Date-Modified = {2019-11-02 19:39:45 +1100},
	Eprint = {1603.04992},
	Journal = {The Computing Research Repository},
	Keywords = {unsupervised},
	Timestamp = {Mon, 13 Aug 2018 16:48:50 +0200},
	Title = {Unsupervised {CNN} for Single View Depth Estimation: Geometry to the Rescue},
	Url = {http://arxiv.org/abs/1603.04992},
	Year = {2016},
	Bdsk-Url-1 = {http://arxiv.org/abs/1603.04992}}

@inproceedings{dataset-nyuv2,
	Author = {Nathan Silberman, Derek Hoiem, Pushmeet Kohli and Rob Fergus},
	Booktitle = {ECCV},
	Date-Added = {2019-11-02 19:36:19 +1100},
	Date-Modified = {2019-11-02 19:36:27 +1100},
	Title = {Indoor Segmentation and Support Inference from RGBD Images},
	Year = {2012}}

@article{dataset-kitti,
	Author = {Andreas Geiger and Philip Lenz and Christoph Stiller and Raquel Urtasun},
	Date-Added = {2019-11-02 19:35:03 +1100},
	Date-Modified = {2019-11-06 16:01:50 +1100},
	Journal = {International Journal of Robotics Research},
	Title = {Vision meets Robotics: The {KITTI} Dataset},
	Year = {2013}}

@article{liu2015supervised,
	Archiveprefix = {arXiv},
	Author = {Fayao Liu and Chunhua Shen and Guosheng Lin and Ian D. Reid},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/bib/journals/corr/LiuSLR15},
	Date-Added = {2019-11-02 17:52:16 +1100},
	Date-Modified = {2019-11-02 17:52:30 +1100},
	Eprint = {1502.07411},
	Journal = {The Computing Research Repository},
	Timestamp = {Mon, 13 Aug 2018 16:48:52 +0200},
	Title = {Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields},
	Url = {http://arxiv.org/abs/1502.07411},
	Year = {2015},
	Bdsk-Url-1 = {http://arxiv.org/abs/1502.07411}}

@article{eigen2014supervised,
	Archiveprefix = {arXiv},
	Author = {David Eigen and Christian Puhrsch and Rob Fergus},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/bib/journals/corr/EigenPF14},
	Date-Added = {2019-11-02 17:51:10 +1100},
	Date-Modified = {2019-11-02 17:51:23 +1100},
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	Journal = {The Computing Research Repository},
	Timestamp = {Mon, 13 Aug 2018 16:47:10 +0200},
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	Bdsk-Url-1 = {http://arxiv.org/abs/1406.2283}}

@inproceedings{zhou2016scale,
	Author = {Dingfu Zhou and Y. Dai and Hongdong Li},
	Booktitle = {2016 IEEE Intelligent Vehicles Symposium (IV)},
	Date-Added = {2019-11-02 11:56:31 +1100},
	Date-Modified = {2019-11-02 11:56:57 +1100},
	Doi = {10.1109/IVS.2016.7535431},
	Keywords = {cameras;computer vision;distance measurement;divide and conquer methods;monocular visual odometry;reliable scale estimation;reliable scale correction;monocular vision system;vision-based autonomous driving;known camera height;ground plane homography decomposition;divide and conquer approach;motion parameters;structure parameters;KITTI standard benchmark dataset;Cameras;Estimation;Geometry;Visualization;Robustness;Roads;Feature extraction},
	Pages = {490-495},
	Title = {Reliable scale estimation and correction for monocular Visual Odometry},
	Year = {2016},
	Bdsk-Url-1 = {https://doi.org/10.1109/IVS.2016.7535431}}

@article{zhou2019scale,
	Archiveprefix = {arXiv},
	Author = {Dingfu Zhou and Yuchao Dai and Hongdong Li},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/bib/journals/corr/abs-1903-00912},
	Date-Added = {2019-11-02 11:54:42 +1100},
	Date-Modified = {2019-11-02 11:54:56 +1100},
	Eprint = {1903.00912},
	Journal = {The Computing Research Repository},
	Timestamp = {Sat, 30 Mar 2019 19:27:21 +0100},
	Title = {Ground Plane based Absolute Scale Estimation for Monocular Visual Odometry},
	Url = {http://arxiv.org/abs/1903.00912},
	Year = {2019},
	Bdsk-Url-1 = {http://arxiv.org/abs/1903.00912}}

@inproceedings{gakne2018scale,
	Author = {Paul Verlaine Gakne and Kyle O'Keefe},
	Date-Added = {2019-11-02 11:48:24 +1100},
	Date-Modified = {2019-11-02 11:53:35 +1100},
	Title = {Tackling The Scale Factor Issue In A Monocular Visual Odometry Using A {3D} City Model},
	Year = {2018}}

@inproceedings{nister2004vo,
	Address = {Los Alamitos, CA, USA},
	Author = {D. Nister and O. Naroditsky and J. Bergen},
	Booktitle = {2013 IEEE Conference on Computer Vision and Pattern Recognition},
	Date-Added = {2019-11-02 11:45:33 +1100},
	Date-Modified = {2019-11-02 11:45:54 +1100},
	Doi = {10.1109/CVPR.2004.1315094},
	Issn = {1063-6919},
	Keywords = {motion estimation;cameras;delay estimation;head;real time systems;navigation;robustness;tracking;layout;global positioning system},
	Pages = {I-652-I-659 Vol.1},
	Publisher = {IEEE Computer Society},
	Title = {Visual odometry},
	Url = {https://doi.ieeecomputersociety.org/10.1109/CVPR.2004.1315094},
	Volume = {1},
	Year = {2004},
	Bdsk-Url-1 = {https://doi.ieeecomputersociety.org/10.1109/CVPR.2004.1315094},
	Bdsk-Url-2 = {https://doi.org/10.1109/CVPR.2004.1315094}}

@book{zisserman2004multiview,
	Author = {Richard Hartley and Andrew Zisserman},
	Date-Added = {2019-11-02 11:09:37 +1100},
	Date-Modified = {2019-11-02 11:11:17 +1100},
	Publisher = {Cambridge University Press},
	Title = {Multiple View Geometry in Computer Vision},
	Year = {2004}}

@inproceedings{vaish2004parallax,
	Author = {Vaish, Vaibhav and Wilburn, B. and Joshi, N. and Levoy, M.},
	Doi = {10.1109/CVPR.2004.1315006},
	Isbn = {0-7695-2158-4},
	Pages = {I-2},
	Title = {Using plane + parallax for calibrating dense camera arrays},
	Volume = {1},
	Year = {2004},
	Bdsk-Url-1 = {https://doi.org/10.1109/CVPR.2004.1315006}}

@incollection{bolles1987epiplane,
	Acmid = {33520},
	Address = {San Francisco, CA, USA},
	Author = {Bolles, Robert C. and Baker, H. Harlyn},
	Chapter = {Epipolar-plane Image Analysis: A Technique for Analyzing Motion Sequences},
	Editor = {Fischler, Martin A. and Firschein, Oscar},
	Isbn = {0-934613-33-8},
	Numpages = {11},
	Pages = {26--36},
	Publisher = {Morgan Kaufmann Publishers Inc.},
	Title = {Readings in Computer Vision: Issues, Problems, Principles, and Paradigms},
	Url = {http://dl.acm.org/citation.cfm?id=33517.33520},
	Year = {1987},
	Bdsk-Url-1 = {http://dl.acm.org/citation.cfm?id=33517.33520}}

@article{yao2016camarray,
	Author = {Yao, Li and Liu, Yunjian and Xu, Weixin},
	Day = {15},
	Doi = {10.1186/s13640-016-0129-2},
	Issn = {1687-5281},
	Journal = {EURASIP Journal on Image and Video Processing},
	Number = {1},
	Pages = {25},
	Title = {Real-time virtual view synthesis using light field},
	Url = {https://doi.org/10.1186/s13640-016-0129-2},
	Volume = {2016},
	Year = {2016},
	Bdsk-Url-1 = {https://doi.org/10.1186/s13640-016-0129-2}}

@inproceedings{adelson1991plenoptic,
	Added-At = {2008-09-01T14:17:15.000+0200},
	Author = {Adelson, Edward H. and Bergen, James R.},
	Biburl = {https://www.bibsonomy.org/bibtex/238ee49cf65e325d5dbf08d1bd12d396a/darnok},
	Booktitle = {Computational Models of Visual Processing},
	Description = {The plenoptic function and the elements of early vision},
	Pages = {3--20},
	Publisher = {MIT Press},
	Title = {The plenoptic function and the elements of early vision},
	Year = 1991}

@phdthesis{dansereau2014phd,
	Author = {Donald Dansereau},
	Date-Added = {2019-10-30 11:45:11 +1100},
	Date-Modified = {2019-10-30 11:48:21 +1100},
	School = {Australian Centre for Field Robotics},
	Title = {Plenoptic Signal Processing for Robust Vision in Field Robotics},
	Year = {2014}}

@article{ihrke2016lfprinciples,
	Author = {Ihrke, Ivo and Restrepo, John and Mignard-Debise, Lo{\"\i}s},
	Doi = {10.1109/MSP.2016.2582220},
	Journal = {IEEE Signal Processing Magazine},
	Pages = {59-69},
	Title = {Principles of Light Field Imaging: Briefly revisiting 25 years of research},
	Volume = {33},
	Year = {2016},
	Bdsk-Url-1 = {https://doi.org/10.1109/MSP.2016.2582220}}

@inproceedings{levoy1996lfrendering,
	Author = {Levoy, Mark and Hanrahan, Pat},
	Booktitle = {Proc. ACM SIGGRAPH},
	Title = {Light Field Rendering},
	Year = {1995}}

@inproceedings{gortler1996lumigraph,
	Acmid = {237200},
	Address = {New York, NY, USA},
	Author = {Gortler, Steven J. and Grzeszczuk, Radek and Szeliski, Richard and Cohen, Michael F.},
	Booktitle = {Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques},
	Doi = {10.1145/237170.237200},
	Isbn = {0-89791-746-4},
	Numpages = {12},
	Pages = {43--54},
	Publisher = {ACM},
	Series = {SIGGRAPH '96},
	Title = {The Lumigraph},
	Url = {http://doi.acm.org/10.1145/237170.237200},
	Year = {1996},
	Bdsk-Url-1 = {http://doi.acm.org/10.1145/237170.237200},
	Bdsk-Url-2 = {https://doi.org/10.1145/237170.237200}}

@incollection{jaderberg2015spatialtransformer,
	Author = {Jaderberg, Max and Simonyan, Karen and Zisserman, Andrew and kavukcuoglu, koray},
	Booktitle = {Advances in Neural Information Processing Systems 28},
	Editor = {C. Cortes and N. D. Lawrence and D. D. Lee and M. Sugiyama and R. Garnett},
	Pages = {2017--2025},
	Publisher = {Curran Associates, Inc.},
	Title = {Spatial Transformer Networks},
	Url = {http://papers.nips.cc/paper/5854-spatial-transformer-networks.pdf},
	Year = {2015},
	Bdsk-Url-1 = {http://papers.nips.cc/paper/5854-spatial-transformer-networks.pdf}}

@inproceedings{zhou2017unsupervised,
	Author = {Zhou, Tinghui and Brown, Matthew and Snavely, Noah and Lowe, David G.},
	Booktitle = {2017 IEEE Conference on Computer Vision and Pattern Recognition},
	Title = {Unsupervised Learning of Depth and Ego-Motion from Video},
	Year = {2017}}

@article{godard2016consistency,
	Archiveprefix = {arXiv},
	Author = {Cl{\'{e}}ment Godard and Oisin {Mac Aodha} and Gabriel J. Brostow},
	Bibsource = {dblp computer science bibliography, https://dblp.org},
	Biburl = {https://dblp.org/rec/bib/journals/corr/GodardAB16},
	Eprint = {1609.03677},
	Journal = {The Computing Research Repository},
	Timestamp = {Mon, 13 Aug 2018 16:46:43 +0200},
	Title = {Unsupervised Monocular Depth Estimation with Left-Right Consistency},
	Url = {http://arxiv.org/abs/1609.03677},
	Year = {2016},
	Bdsk-Url-1 = {http://arxiv.org/abs/1609.03677}}

@article{bian2019consistency,
	Author = {Jia-Wang Bian and Zhichao Li and Naiyan Wang and Huangying Zhan and Chunhua Shen and Ming-Ming Cheng and Ian Reid},
	Date-Modified = {2020-04-10 17:02:28 +1000},
	Title = {Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video},
	Year = {2019}}