Omnidirectional stereo (ODS) is a type of multi-perspective projection that captures horizontal parallax tangential to a viewing circle. This data allows the creation of stereo panoramas that provide plausible stereo views in all viewing directions on the equatorial plane

Christopher Schroers

H. Ishiguro

J Gluckman

K. Tanaka

Kevin Matzen

Robert Anderson

Robert Konrad

S. Peleg

English

Crossref

Omnidirectional Stereo

Richardt, Christian

OPUS

        Citation for published version:Richardt, C 2020, Omnidirectional Stereo. in K Ikeuchi (ed.), Computer Vision: A Reference Guide. Springer.https://doi.org/10.1007/978-3-030-03243-2DOI:10.1007/978-3-030-03243-2Publication date:2020Document VersionEarly version, also known as pre-printLink to publicationUniversity of BathGeneral rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Download date: 05. Jun. 2020Omnidirectional StereoChristian RichardtUniversity of BathSynonymsOmnistereo, ODSRelated ConceptsCalibration of a Non-single Viewpoint SystemImage StitchingOmnidirectional CameraVideo MosaicingDefinitionOmnidirectional stereo (ODS) is a type of multi-perspective projection thatcaptures horizontal parallax tangential to a viewing circle. This data allowsthe creation of stereo panoramas that provide plausible stereo views in allviewing directions on the equatorial plane.BackgroundThe term ‘omnidirectional stereo’ was first coined by Ishiguro et al. [1] in1990, who used it in the context of autonomous mapping and explorationof an unknown environment. Their approach places a video camera on arotating arm that is driven by a stepper motor (see Figure 1). They thentake vertical slit images from the sensor image for creating the left/rightstereo panoramic views. As their primary goal is to map an environment,1they use ODS images for depth estimation of scene points rather than display.They also present a binocular stereo method for depth estimation from twoODS images with a measure for direction-dependent uncertainty.rCFigure 1: Omnidirectional stereo images can be captured with a single cameramounted on an arm of length r that rotates about a point C. Figure adaptedfrom Ishiguro et al. [1].Before the term ‘omnidirectional stereo’ became established with its cur-rent meaning, it was used more broadly for any stereo imaging system, whichcaptures stereo panoramas with disparity, regardless of direction. Gluckmanet al. [2], for example, created a real-time system consisting of two catadiop-tric cameras that are vertically displaced. These cameras capture omnidi-rectional views of an environment that therefore primarily differ by verticaldisparity. While this works just as well for depth estimation, these verticalstereo panoramas are unsuitable for being viewed by humans. This is be-cause our eyes are horizontally displaced and the human visual system thusexpect horizontal disparity, not vertical disparity. In the following, the focustherefore lies on stereo panoramas with horizontal disparity.Since the early days of ODS for mapping and robotics, the main appli-cation has shifted towards display on monitors, projection screens and head-mounted virtual reality displays: Peleg et al. [3] popularized ‘omnistereo’panoramas with automatic disparity control, Richardt et al. [4] proposed im-provements for creating high-quality, high-resolution stereo panoramas, andAnderson et al. [5] and Schroers et al. [6] developed state-of-the-art systemsfor capture and display of real-world virtual reality video. The benefit ofODS video is that time-varying stereo panoramas can easily be packed into atraditional video, which can be processed, stored and transmitted on existingvideo streaming platforms just like any other video. This has established om-nidirectional stereo as a widely supported format by video streaming pipelines2and virtual reality displays.TheoryOmnidirectional stereo is fundamentally a multi-perspective projection thatis created from rays that are tangential to a viewing circle [3]. This pro-jection can, for example, be captured by a slit camera that moves along acircular path and looks in the tangential direction. The slit images capturedat different positions on the viewing circle are mosaicked into a panorama,producing the ODS projection. The two possible tangential directions giverise to the left and right panoramas, as illustrated in Figure 2. The diameterof the viewing circle is usually chosen to be the average human interpupillarydistance of 65mm; however, other sizes are possible.Left panorama Right panoramaFigure 2: Omnidirectional stereo projection creates two panoramas, for theleft and right views, using rays tangential to the viewing circle.As we shall see, most ODS systems do not capture the ODS projec-tion directly. The only implementation of a pair of rotating slit camerasis by Konrad et al. [7]. The key benefit of this approach is that the sys-tem directly captures the ODS projection without requiring computationallyexpensive processing. In addition, this system natively supports scenes con-taining nearby objects, occlusions, thin and repetitive textures, transparentand translucent surfaces, and specular and refractive objects, which remainchallenging for other capture approaches. However, the prototype camerawas limited to only 5 frames per second due to the fast rotation of the cam-era assembly that is required for operation.Ishiguro et al. [1] first described and Peleg et al. [3] later popularizeda single-camera approach that rotates a standard perspective camera on a3larger capture circle that is concentric to the viewing circle. The camera needsto rotate a full 360 degrees to capture a complete ODS panorama, whichassumes a static scene during the capture time. As illustrated in Figure 3,the camera can simultaneously capture rays for both the left and the rightstereo panorama. While this works perfectly in the 2D equatorial plane,out-of-plane rays introduce vertical distortion [5], and perspective camerasintroduce perspective distortion. Richardt et al. [4] proposed techniques forcorrecting perspective distortion and for removing stitching artifacts usingflow-based blending. Stabilization steps were also introduced that reducedrift from image alignment and enable hand-held capture, where the camera’spose often deviates from the ideal position and orientation along the capturecircle.Viewing circle Capture circleFigure 3: A single rotating camera can capture all rays tangential to theviewing circle, by rotating it on a larger circle. Note that this only worksperfectly within the plane containing the viewing and capture circles; otherrays are captured with vertical distortion. Figure adapted from Andersonet al. [5].However, the rotating-camera approach is not practical for capturing ODSvideos, as the camera needs to rotate a full 360 degrees for each video frame.For example, this would require very fast 30 revolutions per second for captur-ing ODS video with 30 frames per second. Peleg et al. [3] explored theoreticaloptical designs involving spiral mirrors and spiral lenses that would enablesingle-shot ODS capture and thus single-camera ODS video. However, thesedesigns were never realized. The TORNADO system by Tanaka and Tachi[8] was the first practical implementation based on these designs. Elongatedprism sheets deflect the light rays entering the cylindrical camera systemand emulate 32 slit cameras that rotate over time. Inside the cylinder, ahyperboloidal mirror reflects light rays into a stationary video camera. Theprojections of the slit cameras into the video camera are separated in two4different ways: (1) based on their spatial location in images, or (2) using lin-ear/circular polarizers. Aggarwal et al. [9] proposed a different approach thatuses a carefully designed mirror with a ‘coffee filter’ shape and reflects multi-ple slit camera images into the video camera without any additional opticalelements. High-resolution simulations validate this concept, but manufac-turing inaccuracies severely reduce the visual quality of real-world captures.Low visual quality and image resolutions are problems shared by all currentcatadioptric single-camera approaches [8, 9].Approaches with multiple omnidirectional cameras improve some of thequality problems caused by complex optical elements. Chapdelaine-Coutureand Roy [10] presented an approach for three or more fisheye cameras that arearranged in a regular polygon, with parallel viewing directions towards thesky. They observed that the planes spanned by the optical axes of adjacentpairs of cameras can be used for cutting their omnidirectional images andstitching them together with minimal disparity mismatch. However, thisapproach can only capture the upper hemisphere of any scene. Matzen et al.[11] proposed a system that uses two consumer spherical cameras, which havetwo 180-degree fisheye lenses each. The cameras are mounted side-by-sidewith a distance of 64mm and the captured imagery is sliced by the planegoing through the cameras (orthogonal to the optical axes) and recombined tocreate the necessary left/right panoramas for ODS imagery. Their approachcancels vertical disparity at the seams using warping in image space, anduses this disparity to correct horizontal disparity. As horizontal disparityis maximal in front of the cameras but zero along the camera baseline, thiscorrection depends on the azimuth angle. In both cases, the resolution ofthe resulting ODS video was not sufficient for high-quality virtual realityexperiences due to limited sensor resolutions [10, 11].The highest visual quality and image resolution of ODS video has beendemonstrated by approaches that use multiple video cameras spaced evenlyon a circle, like a discretized version of the continuously rotating camera ofearlier approaches [1, 3, 4]. Anderson et al. [5] pack 16 GoPro cameras withfisheye optics into a tighly packed ring of 28 cm diameter, demonstratingthat this is a sweet spot between more cameras and a smaller ring diameterthat reduces vertical distortion. Their work comprises a detailed analysisof the sources of vertical parallax and distortion, and presents a flow-basedstitching pipeline that produces temporally coherent ODS video, as availableon YouTube, for example. Schroers et al. [6] also use 16 video cameras, butformulate their video pipeline based on continuous light field reconstruction5from sparse samples. This naturally leads to a panoramic image formationmodel that allows computer-generated imagery to be composited with cap-tured real-world content. They also provide an analysis of the minimumvisible depth that can be stitched or reconstructed, based on the number ofcameras in the rig and their field of view.ApplicationThe initial application for omnidirectional stereo was for mapping and ex-ploring environments using robots [1]. In this scenario, a single rotatingcamera provides a low-cost and effective solution for reconstructing a givenstatic scene. Ishiguro et al. [1] demonstrate how to estimate the depth ofpoints from a single ODS image but also from a binocular pair of ODS im-ages. They further show that the accuracy of depth estimation depends onthe direction relative to the camera baseline, with parallel directions havingthe highest uncertainty. This uncertainty can be decreased by integratingmultiple observations in the form of local maps into a single global map.Since then, omnidirectional stereo has become the de-facto standard pro-jection for stereo panoramas that are used for virtual reality photographyand video. Google’s Cardboard Camera app, for example, is based on theprinciples described by Richardt et al. [4] for creating high-quality, high-resolution stereo panoramas. Multiple independently developed systems forVR videos—including Google Jump [5], Schroers et al. [6] and FacebookSurround360 [12]—have arrived at remarkably similar hardware: multi-viewcamera rigs with 14–16 cameras that are packed into a tight ring to captureomnidirectional stereo video. As of 2019, this defined the state of the art inwidely available virtual reality imagery and video.References[1] Hiroshi Ishiguro, Masashi Yamamoto, and Saburo Tsuji. Omni-directional stereo. IEEE Transactions on Pattern Analysis and Ma-chine Intelligence, 14(2):257–262, February 1992. ISSN 0162-8828. doi:10.1109/34.121792.[2] Joshua Gluckman, Shree K. Nayar, and Keith J. Thoresz. Real-time6omnidirectional and panoramic stereo. In Proceedings of the Image Un-derstanding Workshop, 1998.[3] Shmuel Peleg, Moshe Ben-Ezra, and Yael Pritch. Omnistereo:Panoramic stereo imaging. IEEE Transactions on Pattern Analysisand Machine Intelligence, 23(3):279–290, 2001. ISSN 0162-8828. doi:10.1109/34.910880.[4] Christian Richardt, Yael Pritch, Henning Zimmer, and AlexanderSorkine-Hornung. Megastereo: Constructing high-resolution stereopanoramas. In Proceedings of the International Conference on Com-puter Vision and Pattern Recognition (CVPR), pages 1256–1263, June2013. doi: 10.1109/CVPR.2013.166.[5] Robert Anderson, David Gallup, Jonathan T. Barron, Janne Kontkanen,Noah Snavely, Carlos Hernandez, Sameer Agarwal, and Steven M. Seitz.Jump: Virtual reality video. ACM Transactions on Graphics (Proceed-ings of SIGGRAPH Asia), 35(6):198:1–13, November 2016. ISSN 0730-0301. doi: 10.1145/2980179.2980257.[6] Christopher Schroers, Jean-Charles Bazin, and Alexander Sorkine-Hornung. An omnistereoscopic video pipeline for capture and display ofreal-world VR. ACM Transactions on Graphics, 37(3):37:1–13, August2018. ISSN 0730-0301. doi: 10.1145/3225150.[7] Robert Konrad, Donald G. Dansereau, Aniq Masood, and Gordon Wet-zstein. SpinVR: Towards live-streaming 3D virtual reality video. ACMTransactions on Graphics (Proceedings of SIGGRAPH Asia), 36(6):209:1–12, November 2017. ISSN 0730-0301. doi: 10.1145/3130800.3130836.[8] Kenjie Tanaka and Susumu Tachi. TORNADO: omnistereo video imag-ing with rotating optics. IEEE Transactions on Visualization and Com-puter Graphics, 11(6):614–625, November 2005. ISSN 1077-2626. doi:10.1109/TVCG.2005.107.[9] Rajat Aggarwal, Amrisha Vohra, and Anoop M. Namboodiri. Panoramicstereo videos with a single camera. In Proceedings of the InternationalConference on Computer Vision and Pattern Recognition (CVPR),pages 3755–3763, June 2016. doi: 10.1109/CVPR.2016.408.7[10] Vincent Chapdelaine-Couture and Sébastien Roy. The omnipolar cam-era: A new approach to stereo immersive capture. In Proceedings of theInternational Conference on Computational Photography (ICCP), April2013. doi: 10.1109/ICCPhot.2013.6528311.[11] Kevin Matzen, Michael F. Cohen, Bryce Evans, Johannes Kopf, andRichard Szeliski. Low-cost 360 stereo photography and video capture.ACM Transactions on Graphics (Proceedings of SIGGRAPH), 36(4):148:1–12, July 2017. ISSN 0730-0301. doi: 10.1145/3072959.3073645.[12] Facebook. Surround 360 instruction manual. GitHub, July 2016.URL https://github.com/facebook/Surround360/blob/master/surround360_design/assembly_guide/Surround360_Manual.pdf.8

        Citation for published version:Richardt, C 2020, Omnidirectional Stereo. in K Ikeuchi (ed.), Computer Vision: A Reference Guide. Springer.https://doi.org/10.1007/978-3-030-03243-2DOI:10.1007/978-3-030-03243-2Publication date:2020Document VersionEarly version, also known as pre-printLink to publicationUniversity of BathAlternative formatsIf you require this document in an alternative format, please contact:openaccess@bath.ac.ukGeneral rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright ownersand it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediatelyand investigate your claim.Download date: 07. Jun. 2024Omnidirectional StereoChristian RichardtUniversity of BathSynonymsOmnistereo, ODSRelated ConceptsCalibration of a Non-single Viewpoint SystemImage StitchingOmnidirectional CameraVideo MosaicingDefinitionOmnidirectional stereo (ODS) is a type of multi-perspective projection thatcaptures horizontal parallax tangential to a viewing circle. This data allowsthe creation of stereo panoramas that provide plausible stereo views in allviewing directions on the equatorial plane.BackgroundThe term ‘omnidirectional stereo’ was first coined by Ishiguro et al. [1] in1990, who used it in the context of autonomous mapping and explorationof an unknown environment. Their approach places a video camera on arotating arm that is driven by a stepper motor (see Figure 1). They thentake vertical slit images from the sensor image for creating the left/rightstereo panoramic views. As their primary goal is to map an environment,1they use ODS images for depth estimation of scene points rather than display.They also present a binocular stereo method for depth estimation from twoODS images with a measure for direction-dependent uncertainty.rCFigure 1: Omnidirectional stereo images can be captured with a single cameramounted on an arm of length r that rotates about a point C. Figure adaptedfrom Ishiguro et al. [1].Before the term ‘omnidirectional stereo’ became established with its cur-rent meaning, it was used more broadly for any stereo imaging system, whichcaptures stereo panoramas with disparity, regardless of direction. Gluckmanet al. [2], for example, created a real-time system consisting of two catadiop-tric cameras that are vertically displaced. These cameras capture omnidi-rectional views of an environment that therefore primarily differ by verticaldisparity. While this works just as well for depth estimation, these verticalstereo panoramas are unsuitable for being viewed by humans. This is be-cause our eyes are horizontally displaced and the human visual system thusexpect horizontal disparity, not vertical disparity. In the following, the focustherefore lies on stereo panoramas with horizontal disparity.Since the early days of ODS for mapping and robotics, the main appli-cation has shifted towards display on monitors, projection screens and head-mounted virtual reality displays: Peleg et al. [3] popularized ‘omnistereo’panoramas with automatic disparity control, Richardt et al. [4] proposed im-provements for creating high-quality, high-resolution stereo panoramas, andAnderson et al. [5] and Schroers et al. [6] developed state-of-the-art systemsfor capture and display of real-world virtual reality video. The benefit ofODS video is that time-varying stereo panoramas can easily be packed into atraditional video, which can be processed, stored and transmitted on existingvideo streaming platforms just like any other video. This has established om-nidirectional stereo as a widely supported format by video streaming pipelines2and virtual reality displays.TheoryOmnidirectional stereo is fundamentally a multi-perspective projection thatis created from rays that are tangential to a viewing circle [3]. This pro-jection can, for example, be captured by a slit camera that moves along acircular path and looks in the tangential direction. The slit images capturedat different positions on the viewing circle are mosaicked into a panorama,producing the ODS projection. The two possible tangential directions giverise to the left and right panoramas, as illustrated in Figure 2. The diameterof the viewing circle is usually chosen to be the average human interpupillarydistance of 65mm; however, other sizes are possible.Left panorama Right panoramaFigure 2: Omnidirectional stereo projection creates two panoramas, for theleft and right views, using rays tangential to the viewing circle.As we shall see, most ODS systems do not capture the ODS projec-tion directly. The only implementation of a pair of rotating slit camerasis by Konrad et al. [7]. The key benefit of this approach is that the sys-tem directly captures the ODS projection without requiring computationallyexpensive processing. In addition, this system natively supports scenes con-taining nearby objects, occlusions, thin and repetitive textures, transparentand translucent surfaces, and specular and refractive objects, which remainchallenging for other capture approaches. However, the prototype camerawas limited to only 5 frames per second due to the fast rotation of the cam-era assembly that is required for operation.Ishiguro et al. [1] first described and Peleg et al. [3] later popularizeda single-camera approach that rotates a standard perspective camera on a3larger capture circle that is concentric to the viewing circle. The camera needsto rotate a full 360 degrees to capture a complete ODS panorama, whichassumes a static scene during the capture time. As illustrated in Figure 3,the camera can simultaneously capture rays for both the left and the rightstereo panorama. While this works perfectly in the 2D equatorial plane,out-of-plane rays introduce vertical distortion [5], and perspective camerasintroduce perspective distortion. Richardt et al. [4] proposed techniques forcorrecting perspective distortion and for removing stitching artifacts usingflow-based blending. Stabilization steps were also introduced that reducedrift from image alignment and enable hand-held capture, where the camera’spose often deviates from the ideal position and orientation along the capturecircle.Viewing circle Capture circleFigure 3: A single rotating camera can capture all rays tangential to theviewing circle, by rotating it on a larger circle. Note that this only worksperfectly within the plane containing the viewing and capture circles; otherrays are captured with vertical distortion. Figure adapted from Andersonet al. [5].However, the rotating-camera approach is not practical for capturing ODSvideos, as the camera needs to rotate a full 360 degrees for each video frame.For example, this would require very fast 30 revolutions per second for captur-ing ODS video with 30 frames per second. Peleg et al. [3] explored theoreticaloptical designs involving spiral mirrors and spiral lenses that would enablesingle-shot ODS capture and thus single-camera ODS video. However, thesedesigns were never realized. The TORNADO system by Tanaka and Tachi[8] was the first practical implementation based on these designs. Elongatedprism sheets deflect the light rays entering the cylindrical camera systemand emulate 32 slit cameras that rotate over time. Inside the cylinder, ahyperboloidal mirror reflects light rays into a stationary video camera. Theprojections of the slit cameras into the video camera are separated in two4different ways: (1) based on their spatial location in images, or (2) using lin-ear/circular polarizers. Aggarwal et al. [9] proposed a different approach thatuses a carefully designed mirror with a ‘coffee filter’ shape and reflects multi-ple slit camera images into the video camera without any additional opticalelements. High-resolution simulations validate this concept, but manufac-turing inaccuracies severely reduce the visual quality of real-world captures.Low visual quality and image resolutions are problems shared by all currentcatadioptric single-camera approaches [8, 9].Approaches with multiple omnidirectional cameras improve some of thequality problems caused by complex optical elements. Chapdelaine-Coutureand Roy [10] presented an approach for three or more fisheye cameras that arearranged in a regular polygon, with parallel viewing directions towards thesky. They observed that the planes spanned by the optical axes of adjacentpairs of cameras can be used for cutting their omnidirectional images andstitching them together with minimal disparity mismatch. However, thisapproach can only capture the upper hemisphere of any scene. Matzen et al.[11] proposed a system that uses two consumer spherical cameras, which havetwo 180-degree fisheye lenses each. The cameras are mounted side-by-sidewith a distance of 64mm and the captured imagery is sliced by the planegoing through the cameras (orthogonal to the optical axes) and recombined tocreate the necessary left/right panoramas for ODS imagery. Their approachcancels vertical disparity at the seams using warping in image space, anduses this disparity to correct horizontal disparity. As horizontal disparityis maximal in front of the cameras but zero along the camera baseline, thiscorrection depends on the azimuth angle. In both cases, the resolution ofthe resulting ODS video was not sufficient for high-quality virtual realityexperiences due to limited sensor resolutions [10, 11].The highest visual quality and image resolution of ODS video has beendemonstrated by approaches that use multiple video cameras spaced evenlyon a circle, like a discretized version of the continuously rotating camera ofearlier approaches [1, 3, 4]. Anderson et al. [5] pack 16 GoPro cameras withfisheye optics into a tighly packed ring of 28 cm diameter, demonstratingthat this is a sweet spot between more cameras and a smaller ring diameterthat reduces vertical distortion. Their work comprises a detailed analysisof the sources of vertical parallax and distortion, and presents a flow-basedstitching pipeline that produces temporally coherent ODS video, as availableon YouTube, for example. Schroers et al. [6] also use 16 video cameras, butformulate their video pipeline based on continuous light field reconstruction5from sparse samples. This naturally leads to a panoramic image formationmodel that allows computer-generated imagery to be composited with cap-tured real-world content. They also provide an analysis of the minimumvisible depth that can be stitched or reconstructed, based on the number ofcameras in the rig and their field of view.ApplicationThe initial application for omnidirectional stereo was for mapping and ex-ploring environments using robots [1]. In this scenario, a single rotatingcamera provides a low-cost and effective solution for reconstructing a givenstatic scene. Ishiguro et al. [1] demonstrate how to estimate the depth ofpoints from a single ODS image but also from a binocular pair of ODS im-ages. They further show that the accuracy of depth estimation depends onthe direction relative to the camera baseline, with parallel directions havingthe highest uncertainty. This uncertainty can be decreased by integratingmultiple observations in the form of local maps into a single global map.Since then, omnidirectional stereo has become the de-facto standard pro-jection for stereo panoramas that are used for virtual reality photographyand video. Google’s Cardboard Camera app, for example, is based on theprinciples described by Richardt et al. [4] for creating high-quality, high-resolution stereo panoramas. Multiple independently developed systems forVR videos—including Google Jump [5], Schroers et al. [6] and FacebookSurround360 [12]—have arrived at remarkably similar hardware: multi-viewcamera rigs with 14–16 cameras that are packed into a tight ring to captureomnidirectional stereo video. As of 2019, this defined the state of the art inwidely available virtual reality imagery and video.References[1] Hiroshi Ishiguro, Masashi Yamamoto, and Saburo Tsuji. Omni-directional stereo. IEEE Transactions on Pattern Analysis and Ma-chine Intelligence, 14(2):257–262, February 1992. ISSN 0162-8828. doi:10.1109/34.121792.[2] Joshua Gluckman, Shree K. Nayar, and Keith J. Thoresz. Real-time6omnidirectional and panoramic stereo. In Proceedings of the Image Un-derstanding Workshop, 1998.[3] Shmuel Peleg, Moshe Ben-Ezra, and Yael Pritch. Omnistereo:Panoramic stereo imaging. IEEE Transactions on Pattern Analysisand Machine Intelligence, 23(3):279–290, 2001. ISSN 0162-8828. doi:10.1109/34.910880.[4] Christian Richardt, Yael Pritch, Henning Zimmer, and AlexanderSorkine-Hornung. Megastereo: Constructing high-resolution stereopanoramas. In Proceedings of the International Conference on Com-puter Vision and Pattern Recognition (CVPR), pages 1256–1263, June2013. doi: 10.1109/CVPR.2013.166.[5] Robert Anderson, David Gallup, Jonathan T. Barron, Janne Kontkanen,Noah Snavely, Carlos Hernandez, Sameer Agarwal, and Steven M. Seitz.Jump: Virtual reality video. ACM Transactions on Graphics (Proceed-ings of SIGGRAPH Asia), 35(6):198:1–13, November 2016. ISSN 0730-0301. doi: 10.1145/2980179.2980257.[6] Christopher Schroers, Jean-Charles Bazin, and Alexander Sorkine-Hornung. An omnistereoscopic video pipeline for capture and display ofreal-world VR. ACM Transactions on Graphics, 37(3):37:1–13, August2018. ISSN 0730-0301. doi: 10.1145/3225150.[7] Robert Konrad, Donald G. Dansereau, Aniq Masood, and Gordon Wet-zstein. SpinVR: Towards live-streaming 3D virtual reality video. ACMTransactions on Graphics (Proceedings of SIGGRAPH Asia), 36(6):209:1–12, November 2017. ISSN 0730-0301. doi: 10.1145/3130800.3130836.[8] Kenjie Tanaka and Susumu Tachi. TORNADO: omnistereo video imag-ing with rotating optics. IEEE Transactions on Visualization and Com-puter Graphics, 11(6):614–625, November 2005. ISSN 1077-2626. doi:10.1109/TVCG.2005.107.[9] Rajat Aggarwal, Amrisha Vohra, and Anoop M. Namboodiri. Panoramicstereo videos with a single camera. In Proceedings of the InternationalConference on Computer Vision and Pattern Recognition (CVPR),pages 3755–3763, June 2016. doi: 10.1109/CVPR.2016.408.7[10] Vincent Chapdelaine-Couture and Sébastien Roy. The omnipolar cam-era: A new approach to stereo immersive capture. In Proceedings of theInternational Conference on Computational Photography (ICCP), April2013. doi: 10.1109/ICCPhot.2013.6528311.[11] Kevin Matzen, Michael F. Cohen, Bryce Evans, Johannes Kopf, andRichard Szeliski. Low-cost 360 stereo photography and video capture.ACM Transactions on Graphics (Proceedings of SIGGRAPH), 36(4):148:1–12, July 2017. ISSN 0730-0301. doi: 10.1145/3072959.3073645.[12] Facebook. Surround 360 instruction manual. GitHub, July 2016.URL https://github.com/facebook/Surround360/blob/master/surround360_design/assembly_guide/Surround360_Manual.pdf.8

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