Patent Publication Number: US-11025955-B2

Title: Methods, devices and stream for encoding and decoding volumetric video

Description:
This application claims the benefit, under 35 U.S.C. § 365 of International Application PCT/EP2018/069013, filed Jul. 12, 2018, which was published in accordance with PCT Article 21(2) on Jan. 17, 2019, in English, and which claims the benefit of European Patent Application No. 17305936.1 filed Jul. 13, 2017. 
     1. TECHNICAL FIELD 
     The present disclosure relates to the domain of volumetric video content. The present disclosure is also understood in the context of the formatting of the data representative of the volumetric content, for example for an immersive rendering on end-user devices such as mobile devices or Head-Mounted Displays. 
     2. BACKGROUND 
     This section is intended to introduce the reader to various aspects of art, which may be related to various aspects of the present disclosure that are described and/or claimed below. This discussion is believed to be helpful in providing the reader with background information to facilitate a better understanding of the various aspects of the present invention. Accordingly, it should be understood that these statements are to be read in this light, and not as admissions of prior art. 
     Immersive video, also called 360° flat video, allows the user to watch all around himself through rotations of his head around a still point of view. Rotations only allow a 3 Degrees of Freedom (3DoF) experience. Even if 3DoF video is sufficient for a first omnidirectional video experience, for example using a Head-Mounted Display device (HMD), 3DoF video may quickly become frustrating for the viewer who would expect more freedom, for example by experiencing parallax. In addition, 3DoF may also induce dizziness because of a user never only rotates his head but also translates his head in three directions, translations which are not reproduced in 3DoF video experiences. 
     Volumetric video (also known as 6 Degrees of Freedom (6DoF) video) is an alternative to 3DoF video. When watching a 6DoF video, in addition to rotations, the user can also translate his head inside the watched content and experience parallax. Such videos considerably increase the feeling of immersion and the perception of the scene depth but also prevent from dizziness by providing consistent visual feedback during head translations. The associated content is basically created by the means of dedicated sensors allowing the simultaneous recording of color and depth of the scene of interest. The use of rig of color cameras combined with photogrammetry techniques is a common way to do this recording. 
     While 3DoF videos comprise a sequence of images resulting from the un-mapping of texture images (e.g. spherical images encoded according to latitude/longitude projection or equirectangular projection), 6DoF video frames embed information from several points of views. They can be viewed as a temporal series of point clouds resulting from a three-dimension capture. Two kinds of volumetric videos may be considered depending on the viewing conditions. A first one (i.e. complete 6DoF) allows a complete free navigation inside the video content whereas a second one (aka. 3DoF+) restricts the user viewing space to a limited volume, allowing limited translation of the head and parallax experience. This second context is a natural compromise between free navigation and passive viewing conditions of a seated audience member. 
     Encoding point clouds in a sequence of frames (i.e. a video content) in a manner that is in line with standard video pipeline (e.g. MPEG), taking advantage of compression and transport standards, and that allows a decoding at a video frame rate (i.e. at least 24 images/point clouds per second) is a challenge. The present principles present methods, devices and stream to address these coding and decoding technical problems. 
     3. SUMMARY 
     References in the specification to “one embodiment”, “an embodiment”, “an example embodiment”, “a particular embodiment” indicate that the embodiment described may include a particular feature, structure, or characteristic, but every embodiment may not necessarily include the particular feature, structure, or characteristic. Moreover, such phrases are not necessarily referring to the same embodiment. Further, when a particular feature, structure, or characteristic is described in connection with an embodiment, it is submitted that it is within the knowledge of one skilled in the art to affect such feature, structure, or characteristic in connection with other embodiments whether or not explicitly described. 
     The present disclosure relates to a method of encoding a point cloud into a stream. The method comprises:
         determining, for the point cloud, a list of patch data items. A patch data item comprises an angular range, a depth range and information identifying an area within a picture. A patch data item being paired with a part of the point cloud;   generating a picture comprising a set of image patches. Each image patch is obtained by projecting a part of the point cloud on the picture according to a data item of the list; and   encoding, in the stream, the picture and the list of data items.       

     The operation of determining, for the point cloud, a list of data items comprises:
         a. projecting a part of the point cloud on a projection map, this part comprising points of the point cloud visible from a point of view;   b. determining patch data items of the list by clustering adjacent pixels of the projection map according to depth information and pairing projected points of the cluster with corresponding patch data item; and   c. removing the part of the point cloud from the point cloud;   d. reiterating a, b and c until the point cloud is empty or the patch data item list is full.       

     According to a particular characteristic, the point cloud comprises points of a group of point clouds of a sequence of point clouds. A unique patch data item list is determined for the group of pictures, each picture of the group being generated for a point cloud of the group of point clouds. The group of pictures is encoded in the stream in association with the unique patch data item list. 
     According to a particular characteristic, pixels of an image patch store a depth value. The depth value is determined according to depth range of the patch data item associated with the image patch. 
     The present disclosure also relates to a device for encoding a point cloud into a stream. The device comprises a memory associated with at least one processor configured to:
         determine, for the point cloud, a list of patch data items, a patch data item comprising an angular range, a depth range and information identifying an area within a picture, a patch data item being paired with a part of the point cloud;   generate a picture comprising a set of image patches, each image patch being obtained by projecting a part of the point cloud on the picture according to a data item of the list; and   encode, in the stream, the picture and the list of data items.       

     The present disclosure also relates to a method of decoding a point cloud from a stream. The method comprises:
         decoding a picture and a patch data item list from the stream, a patch data item comprising an angular range, a depth range and information identifying an area within a picture;   unpacking image patches from the picture and associating each image patch with a patch data item of the patch data item list; and   decoding points of the point cloud by un-projecting pixels of each unpacked image patch according to the associated patch data item.   The present disclosure also relates to device for decoding a point cloud from a stream. The device comprises a memory associated with at least a processor configured to:   decode a picture and a patch data item list from the stream, a patch data item comprising an angular range, a depth range and information identifying an area within a picture;   unpacking image patches from the picture and associating each image patch with a patch data item of the patch data item list; and   decoding points of the point cloud by un-projecting, from the point of view, pixels of each unpacked image patch according to the associated patch data item.       

     The present disclosure also relates to a stream carrying data representative of at least a point cloud. The stream comprises at least one picture. The pictures comprise image patches and data comprising a patch data item list. A patch data item is associated with an image patch of at least one picture, a patch data item comprising an angular range, a depth range and information identifying an area within the at least one picture. 
     According to a particular characteristic, the stream further carries data representative of a background omnidirectional video. 
    
    
     
       4. LIST OF FIGURES 
       The present disclosure will be better understood, and other specific features and advantages will emerge upon reading the following description, the description making reference to the annexed drawings wherein: 
         FIG. 1  shows a point cloud  10  and a surface  11  built over the point cloud, according to a non-restrictive embodiment of the present principles; 
         FIG. 2  shows an image  20  representing a three-dimension scene comprising a surface representation of several objects captured as a point cloud as illustrated in  FIG. 1 , according to a non-restrictive embodiment of the present principles; 
         FIG. 3  illustrates an example of the encoding, transmission and decoding of a sequence of point clouds, for example the point clouds of  FIG. 2 , according to a non-restrictive embodiment of the present principles; 
         FIG. 4  illustrates a first iteration of the encoding method according to a point of view, according to a non-restrictive embodiment of the present principles; 
         FIG. 5  shows a diagrammatical example of projection map  41  of  FIG. 4 , according to a non-restrictive embodiment of the present principles; 
         FIG. 6  illustrates a second iteration of the encoding method according to the point of view of  FIG. 5 , according to a non-restrictive embodiment of the present principles; 
         FIG. 7  diagrammatical shows the projection map resulting of the projection of the visible points of the remaining point cloud of  FIG. 6 , according to a non-restrictive embodiment of the present principles; 
         FIG. 8  shows a picture comprising image patches encoding depth information of the point cloud of the scene of  FIG. 2 , according to a non-restrictive embodiment of the present principles; 
         FIG. 9  shows a picture comprising color image patches of the patch data item list determined for the point cloud of the scene illustrated on  FIG. 2 , according to a non-restrictive embodiment of the present principles; 
         FIG. 10  shows an example architecture of a device which may be configured to implement a method described in relation with  FIGS. 12 and/or 13 , according to a non-restrictive embodiment of the present principles; 
         FIG. 11  shows an example of an embodiment of the syntax of a stream when the data are transmitted over a packet-based transmission protocol, according to a non-restrictive embodiment of the present principles; 
         FIG. 12  illustrates a method for encoding a point cloud in a stream, in a device  10  of  FIG. 10  configured to be a device  31  of  FIG. 3 , according to a non-restrictive embodiment of the present principles; 
         FIG. 13  illustrates a method for decoding a point cloud from a stream, in a device of  FIG. 10  configured to be a device  33  of  FIG. 3 , according to a non-restrictive embodiment of the present principles. 
     
    
    
     5. DETAILED DESCRIPTION OF EMBODIMENTS 
     The subject matter is now described with reference to the drawings, wherein like reference numerals are used to refer to like elements throughout. In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the subject matter. It can be evident, however, that subject matter embodiments can be practiced without these specific details. 
     The present description illustrates the principles of the present disclosure. It will thus be appreciated that those skilled in the art will be able to devise various arrangements that, although not explicitly described or shown herein, embody the principles of the disclosure. 
     The present principles will be described in reference to a particular embodiment of a method of encoding a sequence of point clouds in a stream according to a point of view and a method of decoding the sequence of point clouds from the stream according to a point of view. 
     The encoding method obtains a sequence of point clouds as entry. In a first operation, points of a point cloud of the sequence are iteratively projected on a projection map to determine patches. Depth (i.e. the distance between a point and the point of view) is stored in the projection map pixels. In a variant, color information of the projected points is also stored in the projection map. A patch corresponds to a part of the projected points which define an area of adjacent pixels in the projection map and which are depth consistent. The part is defined by the angular range the corresponding projected points occupy in the space from the point of view. For an iteration, only points visible from the point of view are projected. Patches are clustered in the projection map according to their connectivity and depth and added to a patch data item list. Projected points are removed from the point cloud and a new iteration is performed with the modified point cloud until the point cloud is empty or until the patch data item list is full. In a second operation, when the patch data item list is completed, patches are arranged in a picture with a given angular resolution (e.g. 3 seconds per pixel or 5 seconds per pixel) according to the size that the projection of points of the patch will occupy in the picture. The arrangement consists in reserving an area in the picture for projecting (depth and color) the points associated with the patch. The size of the reserved area depends on the picture angular resolution and on the angular range of the patch. The location of the areas in the frame is optimized to cover the picture&#39;s frame without overlapping. In a third operation, points of the point cloud are then projected on the picture according to the patch that they are associated with in the related area. The obtained picture is encoded in the stream in association with data representative of the patch data item list. These data comprise the angular range of the patch, the depth range of the patch (i.e. the minimal and maximal depth of points of the patch) and the location of the patch area within the picture. So, the picture comprises image patches encoding points depth information. In a variant, the picture or a second picture also encodes points color information. In another embodiment, a group of point clouds of the sequence, gathered as a unique point cloud, is used as the entry point cloud of the encoding method. The patch data item list obtained by the iterative operation has the advantage of being temporally consistent. A unique set of data representative of the patch data item list is encoded in the stream and associated with the group of pictures (GoP), a picture being generated for each point cloud of the group. The generated stream has the advantage to be in line with standard video compression and transport pipelines. 
     The decoding method obtains the stream as entry. Pictures and associated data representative of a patch data item list are decoded from the stream. A picture is associated with a patch data item list. A patch data item list may be associated with a group of pictures (GoP). The sequence of point clouds is retrieved from the sequence of pictures, a point cloud of the sequence being obtained by un-projecting pixels of image patches comprised in a picture according to associated patch data. The location of a point is determined according to the depth information stored in the pixel, the coordinates of the pixel in the image patch and the patch data. The angle relatively to the point of view and the distance between the point and the point of view are determined and the point is placed in the point cloud. In a variant, the picture or a second picture comprises color information which is attributed to the un-projected point. The decoding method has the advantage to be straightforward and can be performed at least at a video frame rate by a processor. 
       FIG. 1  shows a point cloud  10  and a surface  11  built over the point cloud. The point cloud  10  corresponds to a large collection of points representing the external surface or the external shape of an object or a group of objects. A point cloud may be seen as a vector based structure, wherein each point has its coordinates. For instance, a vector may be defined by three-dimensional coordinates XYZ in a frame of reference centered on an origin point. In another example, vectors are defined by radial coordinates (θ,φ,d) where (θ,φ) represents a three-dimension direction relative to a point of view and d the distance (also called ‘depth’) between the point of view and the point. A point may also have a color component that may be expressed in any color space, for example RGB (Red, Green and Blue) or YUV (Y being the luma component and UV two chrominance components). A surface  11  may be defined from the point cloud. The surface may be obtained according to several methods. For instance, points may be “splatted”. Size of points is increased up to overlap neighbour to neighbour. These splats are represented as disks whose components (e.g. color) vary diametrically in normal (e.g. Gaussian) manner. Flat disks form a surface that is smoothed. In a variant, a triangulation may be performed on the points and the surface defined by a smoothed mesh based on the triangulation. The surface  11  may be computed by a graphic processor. It is used to determine visibility of points from a point of view. In the example of  FIG. 1 , for example, some points of the neck behind the chin, visible on the point cloud representation  10  are not visible on the surface representation  11  because the surface fills the space gap between points. With a surface representation, it is possible to determine whether a point of the point cloud is visible or not from a point of view. 
       FIG. 2  shows an image  20  representing a three-dimension scene comprising a surface representation of several objects captured as a point cloud. The image  20  is generated from a point of view different of the acquisition point of view. For example, the character at the right of the image  20  is not complete, points of his left arm and his back are not available (e.g. they have not been captured) to fulfill the surface representation. The scene represented on the image  20  may be split in two parts. A first part comprising objects that can be encoded in a 3DoF video without degrading the viewing experience may be encoded in a “background” 3DoF video stream. In  FIG. 2 , the background part comprises the floor and the walls of the scene. A foreground part comprises objects for which a 3DoF+ viewing experience is wanted. In the example of  FIG. 2 , the foreground part corresponds to the characters and to the statues. 
       FIG. 3  illustrates an example of the encoding, transmission and decoding of a sequence of point clouds. A sequence of at least one point cloud  30  is encoded in a stream  32  by an encoder  31  according to the principles of the present encoding method. A decoder  33  obtains stream  32  from a source. For example, the source belongs to a set comprising:
         a local memory, e.g. a video memory or a RAM (or Random Access Memory), a flash memory, a ROM (or Read Only Memory), a hard disk;   a storage interface, e.g. an interface with a mass storage, a RAM, a flash memory, a ROM, an optical disc or a magnetic support;   a communication interface, e.g. a wireline interface (for example a bus interface, a wide area network interface, a local area network interface) or a wireless interface (such as a IEEE 802.11 interface or a Bluetooth® interface); and   a user interface such as a Graphical User Interface enabling a user to input data.       

     Decoder  33  decodes a sequence of point clouds  34  from stream  32  according to the decoding method. According to the present principles, sequence of point clouds  34  is as similar to sequence of point clouds  30  as possible. Sequence of point clouds  34  may be obtained from a source by a rendered  35 . Renderer  35  computes images to be displayed for a 3DoF+ video viewing experience. 
       FIG. 4  illustrates a first iteration of the encoding method according to a point of view  40 . In example of  FIG. 4 , the point cloud comprises three objects  42 ,  43  and  44 . Points of object  42  form a surface with a front side and a back side according to point of view  40 . Backside points of object  42  are not visible from point of view  40 . Points of objects  43  and  44  form surfaces with a front side only according to the point of view  40 . Points of object  43  are visible from point of view  40  and only a part of the points of object  44  are visible from the point of view because of the occultation by the surface of object  43 . In a first iteration of the encoding method, points of the point cloud visible from the point of view are projected on a projection map  41  according to a projection method. On the example of  FIG. 4 , the projection method is a spherical projection, for example a latitude/longitude projection or an equirectangular projection (aka. ERP), so the projection map is represented as a sphere on  FIG. 4 . In a variant, the projection method is a cubical projection method, a pyramid projection method or any projection method centered on a point of view. Points of the frontside of object  42  are projected in an area  45  of the projection map. Backside points of object  42  are not project as they are not visible from view point  40 . Every point of object  43  is visible from point of view  40 . They are projected according to the projection method on area  46  of projection map  41 . Only a part of points of object  44  is visible from point of view  40 . Visible points of object  44  are projected on area  47  of projection map  41 . 
       FIG. 5  shows a diagrammatical example of projection map  41  of  FIG. 4 . Pixels of area  45  store the depth information relative to visible points of visible points of object  42 ; pixels of area  46  store the depth information relative to visible points of visible points of object  43 ; and pixels of area  47  store the depth information relative to visible points of visible points of object  44 . A pixel clustering operation is performed to cluster adjacent pixels of projection map  41  according to depth information. Pixels  45  constitute a adjacent cluster which may be delimited by a rectangle  55 . Pixels  46  and  47  constitute a adjacent area of projection map  41 . Pixels of area  46  and area  47  however differ on the depth value they store. Pixels  46  have a depth value notably smaller than the depth value of pixels  47 . According to the present principles of the encoding method, clusters are determined according to their connection and their depth value. As there is a gap between pixels  46  and pixels  47 , they are grouped in separate clusters. These two clusters may be represented as rectangles  56  and  57 . High frequency area between the two areas may be absorbed by the clustering operation and rectangles  56  and  57  may lightly overlap. Rectangle areas defined by the clustering operation are stored in memory as patch data items. For example, patch data for rectangle  57  comprise the angular range ([θ min , θ max ],[φ min , φ max ]) of the visible points of object  44  according to point of view  40 ; θ min  being the leftmost value of radial coordinates of points of the patch according to the point of view, θ max  being the rightmost, φ min  being the downmost and φ max  being the upmost. The depth range [ρ min ,ρ max ] of the pixel area is also registered in the patch data. This component of patches is useful for encoding to increase dynamics of the byte range reserved for depth encoding. In a variant, clustering operation provide ellipsoid areas and patches comprise data representative of an ellipsoid area. Patches are added to a patch data item list associated with the point cloud. At this step, points of the point cloud visible from the point of view have been projection on the projection map and are removed from the point cloud. 
       FIG. 6  illustrates a second iteration of the encoding method according to point of view  40 . At this step, already projected points have been removed from the point cloud. From points of the object, points  62  forming the back side of object  42  remain. Every point of object  43  have been remove from the point cloud as already projected and points  64  of object  44  remain to be projected. The projection of visible points as described in reference to  FIG. 4  is iterated. 
       FIG. 7  diagrammatical shows the projection map resulting of the projection of the visible points of the remaining point cloud of  FIG. 6 . Rectangle  72  delimits a cluster corresponding to the projection of points  62 . Rectangle  74  delimits a cluster corresponding to the projection of the visible points of the set of points  64 . New patches are determined, two in the example of  FIG. 7 , each patch comprising an angular range ([θ min , θ max ],[φ min , φ max ]) and a depth range [ρ min ,ρ max ]. Projected points are removed from the point cloud. After this iteration, the point cloud comprises only a part of points  64 . A third iteration of the peeling operation is performed as described in reference to  FIGS. 4 to 7 . 
     The peeling operation aims at determining the patch data item list to which each point of the point cloud is going to be associated. This operation may be split into three steps. At each iteration:
         i. The part of the point cloud not already processed called “active set” is projected on a low-resolution projection map which origin is set at the decided viewing point. In the example of  FIGS. 4 to 7 , the chosen projection method is an equirectangular projection. In variants, the projection method maybe another spherical projection method as a latitude/longitude projection or a cubical projection or a pyramid projection or any projection method centered on the point of view. The resolution of the projection map is low (e.g. 1 pixel per degree or 2 pixels per degree) in order to prevent the clustering operation from generating too little patches and thus produce an excessive number of patches.   ii. Then a clustering operation is performed in the projection map to identify homogeneous areas. In the examples of  FIGS. 4 to 9 , identified areas are rectangular. In variants, identified areas may have an ellipsoid shape. An area P covers a set of adjacent pixels of the projection map where a projection occurred and which is depth-consistent. The depth consistency check comes down to considering the distance Z between the viewing point and each projected point covered by P, and ensuring that the distance range of these pixels is not deeper than a threshold T. This threshold may depend on Z max  (the maximum distance between the viewing point and the projected pixels covered by P), on the dynamic D of the depth stored in the generated picture by the further generating operation, and on perceptual properties. For example, the typical human visual acuity is about three minutes of arc. Determining the threshold T according to these criteria have several advantages. At one hand, an image patch in the picture generated in the further generating operation will cover a depth range consistent with the depth resolution of pixels of the generated picture (e.g. 10 bits or 12 bits) and, so, be robust to compression artifacts. On the other hand, the depth range is perceptually-driven by the 3DoF+ context. Indeed, human vision does not equally perceive distance for close or far points. As an example, the threshold may be defined according to equation [eq. 1].       

     
       
         
           
             
               
                 
                   
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     Where VA is a value for visual acuity.
         iii. Points of the active set of points which have been projected are associated to one newly created patch; a patch comprising data representative of the angular range of a clustered area and the depth range of this area. These points discarded from the set of active points. If the set of active points is empty, the peeling process is completed.       

     Once the patch data item list has been determined and each point of the point cloud is paired with one patch of the patch data item list. Each patch comprises data corresponding to a space delimited by two portions of concentric spheres centered on the point of view and is characterized by: an angular range [θ min , θ max ] belonging to [−π; π] radians and [φ min , φ max ] belonging to [−π/2; π/2] radians and a depth range [ρ min , ρ max ]. The used projection method is centered on the point of view. Such a projection method, (e.g. an equirectangular projection) is only angle-dependent: a big object far from the center of projection (i.e. the point of view) may take the same area in the projection map than a small close object. According to the present principles, it is so possible to adapt the patch size according to the importance of the object from the point of view and not according to the intrinsic size of projected object. Such a property is in line with a 3DoF+ context. 
       FIG. 8  shows a picture comprising image patches encoding depth information of the point cloud of the scene of  FIG. 2 . In this example, the peeling operation has been performed on the point cloud of the scene of  FIG. 2 . A list of patches has been determined. The projection of points paired with a patch will generate image patches. Image patches have a resolution called “Atlas Resolution” which defines the quality of the point cloud encoding. For example, an atlas resolution from 18 to 25 pixels per degree allows the encoding of complex scene like the scene of  FIG. 2  in a 2048×2048 pixels picture containing a large number of image patches (e.g. 500 or 600 patches). The lower this resolution is, the worse the final quality. To ensure a good alignment of the image patches on the grid of the picture, the projection map resolution may be chosen as an integral divider of the atlas resolution. 
     A packing operation of image patches is performed. Numerous heuristic algorithms exist to solve the NP-complete problem of packing rectangular cells into a rectangular bin (i.e. the picture to be generated), as the algorithm described in “A Thousand Ways to Pack the Bin” by Jukka Jylanki for instance or the “MaxRects” algorithm (i.e. Single Bin—Best Short Side First configuration) which provides good filling ratio at quite low computational costs. At the end of the packing operation, a location (x, y) of the image patch in the picture (e.g. lower left corner position), and, according to the packing algorithm, a boolean value indicating whether the image patch has been rotated are assigned to each patch of the patch data item list. The packing may be optimized by aligning the patches on Coding Units of the video encoder in order to improve the coding stage.  FIG. 8  shows a picture in which are packed image patches of the patch data item list determined for the point cloud of the scene illustrated on  FIG. 2 . Pixels of the picture of FIG.  8  comprise depth information (i.e. the distance between points of the point cloud and the point of view). 
       FIG. 9  shows a picture comprising color image patches of the patch data item list determined for the point cloud of the scene illustrated on  FIG. 2 . In an embodiment, depth and color information are encoded in pixels of a unique picture. In another embodiment, depth and color information are encoded in two pictures. 
     According to the present principles, a point cloud of the sequence of point clouds is encoded as a picture comprising packed image patches associated with data representative of a patch data item list. The encoding of a point cloud as a picture associated with data has the advantage to be in line with standard compression and transport video pipelines. It is usual, for compression reasons, to gather series of pictures in Group of Pictures (GoP). According to an embodiment of the present encoding method, successive point clouds of the sequence of point clouds to encode are gathered together as a unique point cloud. This grouped point cloud goes through the peeling operation and the packing operation. A unique patch data item list is determined for every point of cloud of the group. The packing structure of the picture is computed for the whole GoP. This structure is preserved during one group of pictures as it notably reduces the video encoding bitrate, especially when the encoder is setup to disable open-gop optimization. Once the packing structure has been determined, each point of the group of point clouds is paired with one patch in the pairing step. Color and depth pictures comprise the results of the splatted projection of each point on image patches. Pictures of the group of pictures and data representative of the patch data item list are encoded in the stream. 
       FIG. 10  shows an example architecture of a device  10  which may be configured to implement a method described in relation with  FIGS. 12 and/or 13 . The device  10  may be configured to be an encoder  31 , a decoder  33  and/or a renderer  35  of  FIG. 3 . 
     The device  10  comprises following elements that are linked together by a data and address bus  101 :
         a microprocessor  102  (or CPU), which is, for example, a DSP (or Digital Signal Processor);   a ROM (or Read Only Memory)  103 ;   a RAM (or Random Access Memory)  104 ;   a storage interface  105 ;   an I/O interface  106  for reception of data to transmit, from an application; and   a power supply, e.g. a battery.       

     In accordance with an example, the power supply is external to the device. In each of mentioned memory, the word «register» used in the specification may correspond to area of small capacity (some bits) or to very large area (e.g. a whole program or large amount of received or decoded data). The ROM  103  comprises at least a program and parameters. The ROM  103  may store algorithms and instructions to perform techniques in accordance with present principles. When switched on, the CPU  102  uploads the program in the RAM and executes the corresponding instructions. 
     The RAM  104  comprises, in a register, the program executed by the CPU  102  and uploaded after switch-on of the device  10 , input data in a register, intermediate data in different states of the method in a register, and other variables used for the execution of the method in a register. 
     The implementations described herein may be implemented in, for example, a method or a process, an apparatus, a computer program product, a data stream, or a signal. Even if only discussed in the context of a single form of implementation (for example, discussed only as a method or a device), the implementation of features discussed may also be implemented in other forms (for example a program). An apparatus may be implemented in, for example, appropriate hardware, software, and firmware. The methods may be implemented in, for example, an apparatus such as, for example, a processor, which refers to processing devices in general, including, for example, a computer, a microprocessor, an integrated circuit, or a programmable logic device. Processors also include communication devices, such as, for example, computers, cell phones, portable/personal digital assistants (“PDAs”), and other devices that facilitate communication of information between end-users. 
     In accordance with an example of encoding or an encoder  31  of  FIG. 3 , the sequence of at least one point of cloud  30  is obtained from a source. For example, the source belongs to a set comprising:
         a local memory ( 103  or  104 ), e.g. a video memory or a RAM (or Random Access Memory), a flash memory, a ROM (or Read Only Memory), a hard disk;   a storage interface ( 105 ), e.g. an interface with a mass storage, a RAM, a flash memory, a ROM, an optical disc or a magnetic support;   a communication interface ( 106 ), e.g. a wireline interface (for example a bus interface, a wide area network interface, a local area network interface) or a wireless interface (such as a IEEE 802.11 interface or a Bluetooth® interface); and   a user interface such as a Graphical User Interface enabling a user to input data.       

     In accordance with examples of the decoding or decoder(s)  33  of  FIG. 3 , the stream is sent to a destination; specifically, the destination belongs to a set comprising:
         a local memory ( 103  or  104 ), e.g. a video memory or a RAM, a flash memory, a hard disk;   a storage interface ( 105 ), e.g. an interface with a mass storage, a RAM, a flash memory, a ROM, an optical disc or a magnetic support; and   a communication interface ( 106 ), e.g. a wireline interface (for example a bus interface (e.g. USB (or Universal Serial Bus)), a wide area network interface, a local area network interface, a HDMI (High Definition Multimedia Interface) interface) or a wireless interface (such as a IEEE 802.11 interface, WiFi® or a Bluetooth® interface).       

     In accordance with examples of encoding or encoder, a bitstream comprising data representative of the volumetric scene is sent to a destination. As an example, the bitstream is stored in a local or remote memory, e.g. a video memory ( 104 ) or a RAM ( 104 ), a hard disk ( 103 ). In a variant, the bitstream is sent to a storage interface ( 105 ), e.g. an interface with a mass storage, a flash memory, ROM, an optical disc or a magnetic support and/or transmitted over a communication interface ( 106 ), e.g. an interface to a point to point link, a communication bus, a point to multipoint link or a broadcast network. 
     In accordance with examples of decoding or decoder or renderer  35  of  FIG. 3 , the bitstream is obtained from a source. Exemplarily, the bitstream is read from a local memory, e.g. a video memory ( 104 ), a RAM ( 104 ), a ROM ( 103 ), a flash memory ( 103 ) or a hard disk ( 103 ). In a variant, the bitstream is received from a storage interface ( 105 ), e.g. an interface with a mass storage, a RAM, a ROM, a flash memory, an optical disc or a magnetic support and/or received from a communication interface ( 105 ), e.g. an interface to a point to point link, a bus, a point to multipoint link or a broadcast network. 
     In accordance with examples, the device  10  is configured to implement a method described in relation with  FIG. 12 , and belongs to a set comprising:
         a mobile device;   a communication device;   a game device;   a tablet (or tablet computer);   a laptop;   a still picture camera;   a video camera;   an encoding chip;   a server (e.g. a broadcast server, a video-on-demand server or a web server).       

     In accordance with examples, the device  10  is configured to implement a rendering method described in relation with  FIG. 13 , and belongs to a set comprising:
         a mobile device;   a communication device;   a game device;   a set top box;   a TV set;   a tablet (or tablet computer);   a laptop; and   a display (such as a HMD for example).       

       FIG. 11  shows an example of an embodiment of the syntax of a stream when the data are transmitted over a packet-based transmission protocol.  FIG. 11  shows an example structure  1100  of a volumetric video stream. The structure consists in a container which organizes the stream in independent syntax elements. The structure may comprise a header part  1101  which is a set of data common to every syntax elements of the stream. For example, the header part comprises metadata about syntax elements, describing the nature and the role of each of them. The header part may also comprise the coordinates of the point of view used for the encoding and information about the size and the resolution of pictures. The structure comprises a payload comprising syntax elements  1102  and  1103 . The first syntax element  1102  comprises data representative of pictures comprising image patches. Pictures may have been compressed according to a video compression method. A picture is associated with a patch data item list of the second syntax element  1103 . In an embodiment, the first syntax element comprises a sequence of pairs of pictures, one picture encoding depth information, the paired picture encoding color information. The second syntax element comprises data representative of the patch data item lists associated with pictures of the first syntax element  1102 . A patch data item list may be associated with a group of pictures. The data representative of the patch data item lists may comprise, for each patch of each patch data item list, an angular range, a depth range and a description of the shape and location of the corresponding image patch in at least one picture. 
     For illustration purpose, in the context of ISOBMFF file format standard, color map, depth map and the metadata would typically be referenced in ISOBMFF tracks in a box of type MOOV, with color map and depth map data themselves embedded in media-data box of type mdat. 
       FIG. 12  illustrates a method for encoding a point cloud in a stream, in a device  10  (described with regard to  FIG. 10 ) configured to be a device  31  of  FIG. 3 , according to a non-restrictive embodiment of the present principles. 
     In a step  1200 , the different parameters of the device  10  are updated. In particular, the point cloud is obtained from a source, a point of view is determined in the space of the point cloud, a projection method is initialized, sizes and resolutions of the projection map and pictures are determined and an empty patch data item list is created. 
     A patch data item list determining operation  1201  is performed. This operation is an iterative process comprising steps  1202 ,  1203  and  1204 . In step  1202 , points of the point cloud which are visible from the point of view are projection according to the projection method on the projection map. The resolution of the projection map is low (e.g. 1 pixel per degree or 2 pixels per degree) in order to prevent the clustering step  1203  from generating too little patches and thus produce an excessive number of patches. In step  1203 , adjacent pixels of the projection map are clustered according depth information. Patches are added to the patch data item list under construction. Projected points are paired with the corresponding patch. In a step  1204  projected points are removed from the point cloud and the operation  1201  is iterated with the modified point cloud. Iterations are performed until the point cloud is empty. In a variant, the operation  1201  is iterated until the patch data item list is full. The patch data item list is considered as full when the area needed for encoding image patches of the patches of the patch data item list is bigger than the area of the bin (i.e. the picture in which image patches will be arranged in operation  1205 ). 
     Once the patch data item list is determined, a packing operation  1205  is performed resulting in the generation of the picture. Points of the point cloud are projected in image patches, image patches having the same resolution than the picture. Image patches are arranged in an optimized manner in the picture. 
     In a step  1206 , the picture and associated patch data item list are encoded in the stream according to the syntax described in reference to  FIG. 11 . The encoding method may be repeated for other point clouds of a sequence of point clouds. In an embodiment of the present principles, a group of point clouds of the sequence, gathered as a unique point cloud, is used as the entry point cloud of the encoding method. A patch data item list common to pictures of the generated group of pictures is determined and encoded once in the stream in association with the whole group of pictures. 
       FIG. 13  illustrates a method for decoding a point cloud from a stream, in a device  10  (described with regard to  FIG. 10 ) configured to be a device  33  of  FIG. 3 , according to a non-restrictive embodiment of the present principles. 
     In a step  1300 , the different parameters of the device  10  are updated. In particular, the stream is obtained from a source, a point of view is determined in the space of the point cloud and an un-projection method is initialized. In a variant, the point of view is decoded from the stream. 
     In a step  1301 , a picture and a patch data item list are decoded from the stream. A patch data item list may be associated with a group of pictures. A patch data item comprises an angular range, a depth range and information identifying an area within associated pictures. A picture comprises a set of image patches packed in the pixel grid of the picture. In a step  1302 , image patches are unpacked from the picture according to patch data items. The information identifying an area within the picture comprised in each patch data item describes the location and the shape of the image patch in the pixel grid of the picture. This information, the angular range of the patch data item and the picture resolution are used to unpack image patches. A patch data item also comprises a depth range that is used at step  1303 . Each unpacked image patch is associated with the corresponding patch data item. In a step  1303 , pixels of unpacked images are un-projected according to associated patch data item. The depth information stored in a pixel is decoded according to the depth range allowing an optimal use of the dynamic of the pixel, the depth being encoded for example on 10 bits or 15 bits. The location in space of the decoded point is then computed according to the coordinates of the pixel within the image patch, the angular range and the decoded depth. The direction of the point according to the point of view is, for example, linearly interpolated according to the coordinates of the pixel within the frame of reference of the image patch and the angular range ([θ min , θ max ],[φ min , φ max ]) comprised in the associated patch data item. The point is projected in the determined direction at a distance from the point of view corresponding to the determined depth. If pixels of the picture stores a color value or if a color value is stored in a picture paired with depth picture, this color value is assigned to the projected point. 
     Naturally, the present disclosure is not limited to the embodiments previously described. 
     In particular, the present disclosure is not limited to methods and devices for encoding/decoding a stream carrying data representative of a volumetric scene (i.e. a sequence of three-dimension point clouds) but also extends to methods of encoding/decoding a sequence of two-dimension point clouds and to any devices implementing these method and notably any devices comprising at least one CPU and/or at least one GPU. 
     The present disclosure also relates to a method (and a device configured) for displaying images rendered from the data stream comprising the information representative of the volumetric scene and to a method (and a device configured) for rendering and displaying the object with a flat video. 
     The present disclosure also relates to a method (and a device configured) for transmitting and/or receiving the stream. 
     The implementations described herein may be implemented in, for example, a method or a process, an apparatus, a computer program product, a data stream, or a signal. Even if only discussed in the context of a single form of implementation (for example, discussed only as a method or a device), the implementation of features discussed may also be implemented in other forms (for example a program). An apparatus may be implemented in, for example, appropriate hardware, software, and firmware. The methods may be implemented in, for example, an apparatus such as, for example, a processor, which refers to processing devices in general, including, for example, a computer, a microprocessor, an integrated circuit, or a programmable logic device. Processors also include communication devices, such as, for example, Smartphones, tablets, computers, mobile phones, portable/personal digital assistants (“PDAs”), and other devices that facilitate communication of information between end-users. 
     Implementations of the various processes and features described herein may be embodied in a variety of different equipment or applications, particularly, for example, equipment or applications associated with data encoding, data decoding, view generation, texture processing, and other processing of images and related texture information and/or depth information. Examples of such equipment include an encoder, a decoder, a post-processor processing output from a decoder, a pre-processor providing input to an encoder, a video coder, a video decoder, a video codec, a web server, a set-top box, a laptop, a personal computer, a cell phone, a PDA, and other communication devices. As should be clear, the equipment may be mobile and even installed in a mobile vehicle. 
     Additionally, the methods may be implemented by instructions being performed by a processor, and such instructions (and/or data values produced by an implementation) may be stored on a processor-readable medium such as, for example, an integrated circuit, a software carrier or other storage device such as, for example, a hard disk, a compact diskette (“CD”), an optical disc (such as, for example, a DVD, often referred to as a digital versatile disc or a digital video disc), a random access memory (“RAM”), or a read-only memory (“ROM”). The instructions may form an application program tangibly embodied on a processor-readable medium. Instructions may be, for example, in hardware, firmware, software, or a combination. Instructions may be found in, for example, an operating system, a separate application, or a combination of the two. A processor may be characterized, therefore, as, for example, both a device configured to carry out a process and a device that includes a processor-readable medium (such as a storage device) having instructions for carrying out a process. Further, a processor-readable medium may store, in addition to or in lieu of instructions, data values produced by an implementation. 
     As will be evident to one of skill in the art, implementations may produce a variety of signals formatted to carry information that may be, for example, stored or transmitted. The information may include, for example, instructions for performing a method, or data produced by one of the described implementations. For example, a signal may be formatted to carry as data the rules for writing or reading the syntax of a described embodiment, or to carry as data the actual syntax-values written by a described embodiment. Such a signal may be formatted, for example, as an electromagnetic wave (for example, using a radio frequency portion of spectrum) or as a baseband signal. The formatting may include, for example, encoding a data stream and modulating a carrier with the encoded data stream. The information that the signal carries may be, for example, analog or digital information. The signal may be transmitted over a variety of different wired or wireless links, as is known. The signal may be stored on a processor-readable medium. 
     A number of implementations have been described. Nevertheless, it will be understood that various modifications may be made. For example, elements of different implementations may be combined, supplemented, modified, or removed to produce other implementations. Additionally, one of ordinary skill will understand that other structures and processes may be substituted for those disclosed and the resulting implementations will perform at least substantially the same function(s), in at least substantially the same way(s), to achieve at least substantially the same result(s) as the implementations disclosed. Accordingly, these and other implementations are contemplated by this application.