Three-dimensional video

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Information about Three-dimensional video
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Published on February 26, 2014

Author: marcocagnazzo

Source: slideshare.net

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An overview of current trends and challanges in 3D video systems, in a seminary given at Roma Tre University, Rome, Italy

ThreeThree-dimensional video: Trends and challenges Marco Cagnazzo Maître de conférences Télécom-ParisTech

Télécom-ParisTech  Founded in 1878 as Ecole Supérieure de Télégraphie  The place where the word Telecommunications (Télécommunications) was born  Ecole Nationale Supérieure des Télécommunications from 1943 to 2008, Télécom-ParisTech since then • Member of Institut Mines-Telecom since March 2012 2 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Télécom-ParisTech  7 Masters Of Science in Telecommunications  Active research • • • • • More than 220 researchers ≈400 PhD Students 50 Doctorates awarded per year Dozens of post-doc positions opened every year Over 600 scientific publications per year  CNRS Mixes Research Unity • • • 3 Signal and Image Processing Computer Science and Networks Electronics and Communications 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Summary  Introduction  3D scene acquisition and formats  3D geometry  3D representation: coding  3D services  Conclusions 4 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Summary  Introduction • 3D representation: an old new story? • Depth perception  3D scene acquisition and formats  3D geometry  3D representation: coding  3D services  Conclusions 5 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D imaging: an old new story? The weighing of the heart scene from the Papyrus of Ani, ca. 1200 B.C. FlatPerspective, images Masaccio, Trinità (1425-1427), Cubism was based on the idea of Firenze Santa Maria Novella, distance fog multiple points of view in a incorporating Perspective painted image, as if to simulate the visual P. Picasso, Les Demoiselles d'Avignon, 1907, MOMA, NYC Multi-view experience of being physically in the presence of the subject, and seeing it from different angles (Wikipedia) Piero della Francesca?, Leon Battista Alberti?, Città ideale (1470-1475 circa), Galleria Nazionale delle Marche, Urbino. 6 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Stereoscopic imaging  As soon as photography was born, stereoscopic devices were created  1844: Stereoscope by David Brewster, a device that could take photographic pictures in 3D.  1851: Improvement by Louis Jules Duboscq (picture of Queen Victoria displayed at The Great Exhibition) 7 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Example Stereoscopic view of Manhattan, 1909 8 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Anaglyph image 9 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Movies  1855: the Kinematoscope was invented, ie the Stereo Animation Camera.  1915: The first anaglyph movie was produced in  1922: the first public 3D movie was displayed - The Power of Love  1935: the first 3D color movie was produced  1947: Soviet Union developed 3D films: Robinson Crusoe  ’50: many 3D movies were produced: Bwana Devil, House of Wax, Alfred Hitchcock’s Dial M for Murder (movie was released in 2D because not all cinemas were able to display 3D films).  2000s: Computer graphics and 3D Renaissance (Avatar, etc.) • • • 10 26/02/2014 3D video channels, 3D TV 3D video standards Multi-view, super-multiview, holoscopy… holography? Marco Cagnazzo 3D Video: Trends and Challenges

3D Television     2008: 3D broadcast on Japanese cable channel BS 11 01/01/2010: SKY 3D started broadcasting in S. Korea 24/03/2010: Cablevision (USA) launched a 3D version of its MSG channel 03/04/2010: British Sky Broadcasting launched a limited 3D TV broadcast service.  18/05/2010: Spanish Canal+ started 3D broadcast  28/09/2010: Virgin Media launched a 3D TV on Demand service ...  November 2010: 8 3D channels in Europe  April 2011: HIGH TV, a 3D family entertainment Channel launched  2012: 3D TV launched in China, Italy, and other countries  2013: New 3D programs in Brazil; BBC suspends 3D programs 11 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Television Channel HIGH TV 3D n3D Cinema 3D 3net Eurosport 3D Sky 3D Foxtel 3D HD1 Sky 3D Anixe 3D 3D-TV Sport 5 3D MSG 3D nShow 3D 12 26/02/2014 Country(s) Worldwide United States United States United States Europe United Kingdom and Ireland Australia Belgium (and other European countries) Germany and Austria Germainspeaking countries Finland Israel United States Poland Channel Canal+ 3D Canal+ 3D España NEXT Man 3D NEXT Lejdis 3D NEXT Young 3D Country(s) France Active 3D India BS11 RedeTV! Viasat 3D Brava3D Teledünya 3D Sky 3D Japan Brazil Sweden Europe Turkey South Korea Spain Poland Poland Poland Sukachan 3D169 Japan ESPN 3D Xfinity 3D Penthouse 3D TV Azteca 3D Marco Cagnazzo United States United States Europe Mexico 3D Video: Trends and Challenges

Depth perception  Monocular cues • • • • • • • • 13 26/02/2014 Perspective Motion parallex Depth from motion Distance fog and texture degradation Object sizes Illumination and shades Blur Occlusions Marco Cagnazzo 3D Video: Trends and Challenges

Monocular cues  Perspective, distance fog and texture degradation 14 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Monocular cues  Depth from motion 15 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Monocular cues  Illumination and shadows 16 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Monocular cues  Defocus blur, occlusions 17 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Binocular cues  Stereovision: vergence • Disparity perception  Accommodation (focus) 18 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Video  Nowadays, 3D video is much about a very simple representation of a 3D scene, i.e., a stereoscopic (two views) representation  However, more complete and flexible representations exist, as we will see  Ideally, one would like to reproduce the light field of the original scene 19 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Video Systems 2D/3D conversion 20 26/02/2014 … 3D Video Decoder +DIBR … Multi user 3D TV Single user 3D TV DVB Decoder Multiview + Depth (MVD) 3D Video Coding Depth camera … Multi-camera setup 3D Content Production Stereo camera Video Depth / Geometry Marco Cagnazzo Meta data 3D Video: Trends and Challenges 2D TV

Video services evolution N views # views FTV HD-FTV UD-FTV HD3DTV UD3DTV 2 views 3DTV 720 × 576 TV 1920 × 1080 HDTV 7680 × 4320 UDTV # pixels 21 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Summary  Introduction  3D scene acquisition and formats • Plenoptic function • Stereo, Multiview, MVD, LDV, holoscopy  3D geometry  3D representation: coding  3D services  Conclusions 22 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Video capture  Stereoscopy : 2 cameras mounted side by side, separated by the same distance as between a person's pupils.  Multi-view capture uses arrays of many cameras to capture a 3D scene through multiple independent videos  Color+depth camera: capture normal video and a depth map, estimated with radar-like techniques (using infrared) or structured light  Multiview+depth (MVD): N Color+depth cameras • MVD: the most flexible format (view synthesis at user side)  Holoscopy 23 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Video representation: plenoptic function  The plenoptic function, or light-field of a scene is the complete information about what can be seen from any angle, at any position, in any time, at any frequence (color) y z x 24 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Video representation: plenoptic function  The plenoptic function, or light-field of a scene is the complete information about what can be seen from any angle, at any position, in any time, at any frequence (color) y z x 25 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Video representation: plenoptic function  The plenoptic function, or light-field of a scene is the complete information about what can be seen from any angle, at any position, in any time, at any frequence (color) y z x 26 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D video representation  27 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

From the plenoptic function to the stereo video y z x 28 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

From the plenoptic function to the multiview video y z x 29 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

From the plenoptic function to the super multiview video y z x 30 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Video Acquisition: stereo camera 31 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Video Acquisition: color + depth 32 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Video Acquisition: MVD 33 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D rendering: anaglyph 34 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D rendering: polarized glasses 35 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D rendering: Alternate-frame sequencing  Every second frame is from the left [right] view  Video is projected at twice the frame rate  Viewers wears glasses that shutter alternatively the left or the right eye 36 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Auto stereoscopic display 37 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Traditional 3D rendering: problems  Accommodations (focus) - vergence (disparity) conflict  Cross-talk 38 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

From the plenoptic function to the holoscopy y z x 39 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

From the plenoptic function to the holoscopic format  New format: holoscopy, or integral imaging  Glasses-free 3D, promising no visual pain 3D scene Microlenses array Camera 2D screen Microlenses array 3D rendering Holoscopic image and videos Data redundancy Grid-shaped pattern Compression? 40 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Holoscopy 41 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Other formats: Layered Depth Video and Images 42 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D scene representation: summary # depths (geometrical information) ∞ depths 3D model + texture 1View+ Multi Depth 1 depths 1View+1 Depth 0 depths 2D TV LDV Multiview Super Multiview Holoscopy 1 view 43 26/02/2014 Light field # views ∞ views Marco Cagnazzo 3D Video: Trends and Challenges

Summary  Introduction  3D scene acquisition and formats  3D geometry • Pin-hole camera model • Stereoscopy and disparity  3D representation: coding  3D services  Conclusions 44 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Pin-hole camera model C : optical center f : focal length c : principal point Using the image plane we avoid the image inversion of the retinal plane 45 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Pin-hole camera model  Coordinate systems: • • • • 46 26/02/2014 W.r.t. the optical center (XC,YC,ZC) Wr.t. the image plane (x,y) Wr.t. the principal point (xc,yc) Real world (X,Y,Z) Marco Cagnazzo 3D Video: Trends and Challenges

Pin-hole camera model M m m’ f C Image plane Object plane M m m’ 47 26/02/2014 M’ Zc M’ Marco Cagnazzo 3D Video: Trends and Challenges

Homogeneous coordinates  48 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Intrinsic parameters  Image plane m m’ 49 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Image coordinates  50 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Extrinsic parameters  51 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Image and real coordinates  52 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Stereoscopy The two projections of the same point into the two image planes are called homologous points The stereo matching problem consists in finding the correspondence between homologous points 53 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Epipolar geometry  54 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Parallel cameras     It is a case of particular interest Corresponds to the human vision (frontal vision) Parallel optical axes and same focal length In this case the epipolar lines are parallel to the baseline, and the images are co-planar  Homologous point only differ for the an horizontal component: it is called disparity  It is possible to rectify a couple of camerals, i.e. to produce the images corresponding to the co-planar case 55 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Disparity and depth  B X-B X x M Z x' m Cl 56 26/02/2014 f Cr M’ Marco Cagnazzo 3D Video: Trends and Challenges

Disparity estimation 57 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

The disparity field  58 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

The disparity field: example 59 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

The disparity estimation problem  60 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Difficulties of stereo matching  Occlusions: not all the left image points are visible in the right image  Not perfectly identical cameras and noise make homologous point having different luminance/colour  Untextured regions: this makes difficult evaluating the data attachment term  Complexity of the minimization problem • • • 61 26/02/2014 Full search Convex minimization Parallel algorithms Marco Cagnazzo 3D Video: Trends and Challenges

Post-processing  Often the disparity field can be enhanced using postprocessing • Cross-checking helps in finding occlusion points • Interpolation: it allows to “fill in” occlusions • Median filtering: removes estimated values too different with respect to the neighborhood 62 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Summary     Introduction 3D scene acquisition and formats 3D geometry 3D representation: coding • Multiview video coding • MVD video coding • Holoscopy coding  3D services  Conclusions 63 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Coding of 3D video  Encode separately each view (Simulcast)  Encode jointly view • Use other views to perform prediction of current image  Encode one/more views and a depth maps • Joint or separate coding of view and depth 64 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Compression standards  Frame compatible stereo interleaving  MPEG-2 Multiview Profile I 26/02/2014 B P B B P B I B P 65 B B B B B B B B P B Marco Cagnazzo 3D Video: Trends and Challenges

Compression standards: H.264/MVC P0 B0 B3 B1 B3 P0 B3 B B2 B4 B1 B4 B2 B4 B0 B4 B3 B1 B3 B0 B3 B1 B3 P0 B3 B0 B4 B2 B4 B1 B4 B2 B4 B0 B4 I0 B3 B1 B3 B0 B3 B1 B3 I0 B3 B0 B4 B2 B4 B1 B4 B2 B4 B0 B4 P0 B3 B1 B3 B0 B3 B1 B3 P0 B3 B0 B B2 B4 B1 B4 B2 B4 B0 B4 P0 26/02/2014 B3 P0 66 B1 B0 H.264 MVC extension Base view + dependent views Disparity compensated prediction B3 B3 B1 B3 B0 B3 B1 B3 P0 B3 Marco Cagnazzo 3D Video: Trends and Challenges

3D video coding  3D Video Coding (3DVC)  New phase of standardization in MPEG  Objectives: • Display-independent representation • Advanced stereoscopic display processing: e.g. adjust depth perception by controlling baseline distance • High quality auto-stereoscopic multiview displays: many views with limited bit rate 67 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

MVV vs. MVD  68 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D Video Coding (3DVC) 69 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

3D-HEVC: Coding structure  Coding by access units HEVC Temporal Inter-component Inter-view (texture) Inter-view (depth) HEVC + additional tools 70 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Standardization is on-going  Inter-view tools • Disparity compensated prediction • Inter-view motion prediction • …  Inter-component tools • • • • 71 26/02/2014 Quad-tree initialization/limitation Motion parameter inheritance Intra-prediction inheritance … Marco Cagnazzo 3D Video: Trends and Challenges

Enhancing the use of DCP DV : 9% MV : 91% Intra Temporal Skip 72 26/02/2014 Temporal Inter Interview Inter Interview Skip Marco Cagnazzo 3D Video: Trends and Challenges

Conditional mode inheritance 73 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Criteria for inheritance Sobel Module Angle histogram 60 300 10 50 250 20 30 150 Nbr occurences 40 200 30 40 20 100 50 10 50 60 0 -2 10 20 30 40 50 -1.5 -1 -0.5 60 Module 1 1.5 2 1.5 2 300 250 250 200 30 150 Nbr occurences 350 300 20 0.5 Angle histogram 350 10 0 Angle 200 150 40 100 100 50 50 50 60 10 74 26/02/2014 20 30 40 50 60 0 0 -2 -1.5 -1 -0.5 0 Angle 0.5 Marco Cagnazzo 1 3D Video: Trends and Challenges

Non standard approach: Depth Coding Based on Elastic Deformations 1  1 Base tool: A tool that can find an intermediate contour between an initial and a final one, by generating the geodesic (series of elastic deformations) between the two curves. 2 2 3 4 5 3 6 7 4 75 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges 8

Depth compression: impact on image synthesis 76 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

DIBR: Depth-image based rendering      Given a view, how to synthesize a virtual view point? It is possible if depth is known: Linear operation (omography) in homogenous coordinates Further simpliflied in the rectified case: disparity compensation VSRS: view synthesis reference software Reference image plane Virtual image plane M m' m C2 C1 77 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

VSRS: global scheme Reference homography matrix Single view processing Filling holes Synthesis homography matrix Reference homography matrix 78 26/02/2014 Merging Single view processing Marco Cagnazzo 3D Video: Trends and Challenges

VSRS: single view processing Reference homography matrix Synthesis homography matrix Reference depth Depth Map Synhtesis Synthesized view Homography Matrix View Synhtesis Reference view 79 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Depth map synthesis  Mapping of depth values on the image plane  When tow points are associated to the same coordinates,only the nearest is kept (occlusion)  Some coordinates may have no depth value (disocclusion)  Median filtering removes “small” holes Synthetized depth 80 26/02/2014 Median filtering Marco Cagnazzo 3D Video: Trends and Challenges

View synthesis  Mapping of texture values of the reference image using the synthetized depth  Depth knowledge allows to solve some occlusion conflict Synthesis from the left 81 26/02/2014 Synthesis from the right Marco Cagnazzo 3D Video: Trends and Challenges

Contour correction  False contours may appear in the synthetized view  This can me mitigated if filled regions are artificially increased by one pixel 82 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

View merging  Left and right images are merged, averaging pixels where both views are available  As a consequence, only small holes remain in the merged image 83 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Holes filling: inpainting  84 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Holes filling: inpainting Holes Filling 85 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Encoding holoscopic video  The holoscopic videos (HV) have a lot of redundancy…  … but also a large high-frequency content (grid) • Grid removal?  Benchmark: “2D coding”, i.e. plain HEVC on the HV 86 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Encoding holoscopic video Ad hoc techniques Self-similarities: intra-image motion-estimation View extraction + Multi-view coding Scalable coding Residual encoder Holoscopic Prediction Residual encoder Inter-view Prediction Multiplexer View extraction     2D Encoder 87 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Summary  Introduction  3D scene acquisition and formats  3D geometry  3D representation: coding  3D services • FTV and IMVS  Conclusions 88 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

FTV System Video capture 26/02/2014 Encoding 2D/3D Display 89 Preprocessing View generation Decoding Marco Cagnazzo 3D Video: Trends and Challenges

FTV Display View Synhtesis 3D Display FTV Data Viewpoint control View Synhtesis 90 26/02/2014 2D/3D Display Marco Cagnazzo 3D Video: Trends and Challenges

FTV interactive streaming  FTV can be very heavy, even after compression  In the interactive framework, only 2views + 2 depths could be sent  The current view is synthesized using encoded views  Problem: view switching (among encoded views) affects temporal prediction 91 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

FTV interactive streaming  Multiview video for free viewpoint TV services  Several view available: the user interactively switches from one view to another  View pattern unknown at encoding time 92 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Interactive Multiview Video Streaming Views All frames are Intra Coded Each image is coded and stored only once Large bandwidth requested Relatively low server space requested Time 93 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Interactive Multiview Video Streaming Views P-frames are used: all possible frame dependencies are coded Each image is coded many times Smallest bandwidth requested Very large server space requested Time 94 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Distributed video coding: principle Quantizer Q Turbo Encoder Buffer Q’ Turbo Decoder Min Distort Reconstr Decoded WZFs WZ WZ WZ SI Slepian-Wolf Coder Image Interpolation KF KF Intra Coder Encoder 95 26/02/2014 Intra Decoder Decoded KFs Decoder Marco Cagnazzo 3D Video: Trends and Challenges

Interactive Multiview Video Streaming Views WZ-frames are used: only parity bits are coded Each image is coded and stored only once Trade-off between server space and bandwidth Time 96 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Application to IMVS: Interactive Multiview Video Streaming Bandwidth Only Intra WZ coding Ideal Case: Path known at encoding time Predictive coding: Each image coded many times Operation region Server space 97 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Conclusions  3D video has periodically experienced waves of excitement and deception  A main problem is the visual discomfort related to the stereoscopic representation  The emerging format may solve this problem • Super-multiview, holoscopy  Many problems yet to be solved • Effective compression • Quality evaluation (objective and subjective metrics) • Transmission  Is holography the future? 98 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

Conclusions Contact : cagnazzo@telecom-paristech.fr Bibliography : [1] M. Tanimoto, Overview of free viewpoint television. In Signal Processing: Image Communication Volume 21, Issue 6, July 2006, Pages 454-461 [2] A. Smolic and P. Kauff, Interactive 3-D video representation and coding technologies. Proc. IEEE, 93(1), pp. 98–110, Jan. 2005 [3] G. Cheung, A. Ortega and N. Cheung, Interactive Streaming of Stored Multiview Video Using Redundant Frame Structures, in IEEE Transactions on Image Processing, 20(3), pp.744-761, March 2011 [4] F. Dufaux, B. Pesquet-Popescu, M Cagnazzo (eds.): Emerging Technologies for 3D Video. Wiley, 2013 [5] Faugeras, O. , Three-dimensional computer vision: a geometric viewpoint. MIT Press, Cambridge, MA, 1994 [6] C. Fehn, Depth-Image-Based Rendering (DIBR), Compression and Transmission for a New Approach on 3D-TV, SPIE Electronic imaging 2004 [7] M. Bertalmio, G. Sapiro, C. Ballester and V. Caselles, Image inpainting, Computer Graphics, SIGGRAPH 2000, July 2000, 417–424 99 26/02/2014 Marco Cagnazzo 3D Video: Trends and Challenges

THANKS FOR YOUR ATTENTION! ?? || (1) ______________ (1) 100 26/02/2014 Questions or comments, ® Dario Rossi, Télécom-ParisTech Marco Cagnazzo 3D Video: Trends and Challenges

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