WO2019229293A1 - Appareil, procédé et programme d'ordinateur pour vidéo volumétrique - Google Patents

Appareil, procédé et programme d'ordinateur pour vidéo volumétrique Download PDF

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Publication number
WO2019229293A1
WO2019229293A1 PCT/FI2019/050389 FI2019050389W WO2019229293A1 WO 2019229293 A1 WO2019229293 A1 WO 2019229293A1 FI 2019050389 W FI2019050389 W FI 2019050389W WO 2019229293 A1 WO2019229293 A1 WO 2019229293A1
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Prior art keywords
map
patch
points
texture
material maps
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PCT/FI2019/050389
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English (en)
Inventor
Mika Kalevi Pesonen
Kimmo Tapio Roimela
Johannes PYSTYNEN
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Nokia Technologies Oy
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Publication of WO2019229293A1 publication Critical patent/WO2019229293A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/50—Lighting effects
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T15/00—3D [Three Dimensional] image rendering
    • G06T15/04—Texture mapping
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T17/00—Three dimensional [3D] modelling, e.g. data description of 3D objects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N13/00—Stereoscopic video systems; Multi-view video systems; Details thereof
    • H04N13/20—Image signal generators
    • H04N13/275—Image signal generators from 3D object models, e.g. computer-generated stereoscopic image signals
    • H04N13/279—Image signal generators from 3D object models, e.g. computer-generated stereoscopic image signals the virtual viewpoint locations being selected by the viewers or determined by tracking
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/50—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding
    • H04N19/597—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using predictive coding specially adapted for multi-view video sequence encoding
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2210/00—Indexing scheme for image generation or computer graphics
    • G06T2210/56—Particle system, point based geometry or rendering
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/80—Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
    • H04N21/81—Monomedia components thereof
    • H04N21/816—Monomedia components thereof involving special video data, e.g 3D video

Definitions

  • the present invention relates to an apparatus, a method and a computer program for using physically-based object capture for volumetric video coding and decoding.
  • Volumetric video data represents a three-dimensional scene or object and can be used as input for virtual reality (VR), augmented reality (AR) and mixed reality (MR) applications.
  • VR virtual reality
  • AR augmented reality
  • MR mixed reality
  • Such data describes the geometry, e.g. shape, size, position in three- dimensional (3D) space, and respective attributes, e.g. colour, opacity, reflectance and any possible temporal changes of the geometry and attributes at given time instances.
  • Volumetric video is either generated from 3D models through computer-generated imagery (CGI), or captured from real-world scenes using a variety of capture solutions, e.g. multi camera, laser scan, combination of video and dedicated depth sensors, and more. Also, a combination of CGI and real-world data is possible.
  • CGI computer-generated imagery
  • a method comprising receiving a plurality of material maps associated with an object of a three-dimensional (3D) video stream, wherein a point cloud of the object is represented by at least one 2D patch associated with a depth map; storing the plurality of material maps, wherein the material maps comprise at least one displacement map, at least one normal map and at least one color texture map; receiving an indication of a mapping between points of the material maps and points of the 2D patch; reconstructing geometry of the 2D patch based on the depth map, the displacement map, the normal map and the mapping between points of the stored material maps and the 2D patch; and reconstructing texture of the 2D patch based on the color texture map and the mapping between the points of the stored material maps and the 2D patch.
  • said color texture map comprises only chroma samples of the texture.
  • the method further comprises linearly
  • the method further comprises reconstructing a coarse surface from the depth map; and offsetting the coarse surface by the displacement map to obtain a surface geometry to render.
  • the method further comprises re-lighting at least part of the surfaces of the reconstructed object.
  • An apparatus comprises means for receiving a plurality of material maps associated with an object of a three-dimensional (3D) video stream, wherein a point cloud of the object is represented by at least one 2D patch associated with a depth map; means for storing the plurality of material maps, wherein the material maps comprise at least one displacement map, at least one normal map and at least one color texture map; means for receiving an indication of a mapping between points of the material maps and points of the 2D patch; means for reconstructing geometry of the 2D patch based on the depth map, the displacement map, the normal map and the mapping between points of the stored material maps and the 2D patch; and means for reconstructing texture of the 2D patch based on the color texture map and the mapping between the points of the stored material maps and the 2D patch.
  • a method comprising obtaining a plurality of material maps associated with an object of a three-dimensional (3D) video stream; obtaining a projection of the 3D object represented by a point cloud, wherein the point cloud is represented by at least one 2D patch associated with a depth map;
  • the material maps comprise at least one displacement map, at last one normal map, and at least one color texture map; transmitting said plurality of material maps; and transmitting an indication of the mapping between points of the material maps and points of the 2D patch.
  • said color texture map comprises only chroma samples of the texture.
  • the method further comprises including the depth map data in a bitstream as compressed.
  • the method further comprises creating chroma components for each frame of the video stream; and determining the mapping of chroma components of a 2D patch to chroma components of the material map as a patch chroma offset.
  • the method further comprises obtaining at least one further material map, said material map comprising one or more of the following: an albedo / base color texture map; a roughness map; a metalness map; a cavity map; an ambient occlusion map.
  • An apparatus comprises means for obtaining a plurality of material maps associated with an object of a three-dimensional (3D) video stream; means for obtaining a projection of the 3D object represented by a point cloud, wherein the point cloud is represented by at least one 2D patch associated with a depth map; means for determining a mapping between points of the material maps and points of the 2D patch, wherein the material maps comprise at least one displacement map, at last one normal map, and at least one color texture map; means for transmitting said plurality of material maps; and means for transmitting an indication of the mapping between points of the material maps and points of the 2D patch.
  • Apparatuses comprise at least one processor and at least one memory, said at least one memory stored with code thereon, when executed by said at least one processor, causes the apparatus to perform the above methods.
  • Computer readable storage media comprise code for use by an apparatus, which when executed by a processor, causes the apparatus to perform the above methods.
  • Fig. 1 shows a system for capturing, encoding, decoding, reconstructing and viewing a three-dimensional scheme
  • FIGs. 2a and 2b show a capture device and a viewing device
  • Figs. 3a and 3b show an encoder and decoder for encoding and decoding texture pictures, geometry pictures and/or auxiliary pictures;
  • Figs. 4a, 4b, 4c and 4d show a setup for forming a stereo image of a scene to a user
  • Figs. 5a illustrates projection of source volumes in a scene and parts of an object to projection surfaces, as well as determining depth information
  • Fig. 5b shows an example of projecting an object using a cube map projection format
  • Fig. 6 shows a projection of a source volume to a projection surface, and inpainting of a sparse projection
  • Fig. 7 shows an example of occlusion of surfaces
  • FIG. 8 shows a flow chart for encoding physically-based material representation according to an embodiment
  • Fig. 9 shows an example of mapping UV coordinates of a 2D patch to a plurality of material maps of a scanned object
  • Fig. 10 shows a flow chart for decoding physically-based material representation according to an embodiment
  • Fig. 11 shows a per-patch decoding process according to an embodiment
  • Fig. 12 shows an example for updating material maps during a data stream according to an embodiment.
  • Voxel of a three-dimensional world corresponds to a pixel of a two- dimensional world. Voxels exist in a three-dimensional grid layout.
  • An octree is a tree data structure used to partition a three-dimensional space. Octrees are the three-dimensional analog of quadtrees.
  • a sparse voxel octree (SVO) describes a volume of a space containing a set of solid voxels of varying sizes. Empty areas within the volume are absent from the tree, which is why it is called“sparse”.
  • a three-dimensional volumetric representation of a scene is determined as a plurality of voxels on the basis of input streams of at least one multicamera device.
  • at least one but preferably a plurality (i.e. 2, 3, 4, 5 or more) of multicamera devices are used to capture 3D video representation of a scene.
  • the multicamera devices are distributed in different locations in respect to the scene, and therefore each multicamera device captures a different 3D video representation of the scene.
  • representations captured by each multicamera device may be used as input streams for creating a 3D volumetric representation of the scene, said 3D volumetric representation comprising a plurality of voxels.
  • Voxels may be formed from the captured 3D points e.g. by merging the 3D points into voxels comprising a plurality of 3D points such that for a selected 3D point, all neighbouring 3D points within a predefined threshold from the selected 3D point are merged into a voxel without exceeding a maximum number of 3D points in a voxel.
  • Voxels may also be formed through the construction of the sparse voxel octree. Each leaf of such a tree represents a solid voxel in world space; the root node of the tree represents the bounds of the world.
  • the sparse voxel octree construction may have the following steps: 1) map each input depth map to a world space point cloud, where each pixel of the depth map is mapped to one or more 3D points; 2) determine voxel attributes such as colour and surface normal vector by examining the neighbourhood of the source pixel(s) in the camera images and the depth map; 3) determine the size of the voxel based on the depth value from the depth map and the resolution of the depth map; 4) determine the SVO level for the solid voxel as a function of its size relative to the world bounds; 5) determine the voxel coordinates on that level relative to the world bounds; 6) create new and/or traversing existing SVO nodes until arriving at the determined voxel coordinates; 7) insert the solid voxel as a leaf of the tree, possibly replacing or merging attributes from a previously existing voxel at those coordinates.
  • a volumetric video frame is a complete sparse voxel octree that models the world at a specific point in time in a video sequence.
  • Voxel attributes contain information like colour, opacity, surface normal vectors, and surface material properties. These are referenced in the sparse voxel octrees (e.g. colour of a solid voxel), but can also be stored separately.
  • Point clouds are commonly used data structures for storing volumetric content. Compared to point clouds, sparse voxel octrees describe a recursive subdivision of a finite volume with solid voxels of varying sizes, while point clouds describe an unorganized set of separate points limited only by the precision of the used coordinate values.
  • each frame may produce several hundred megabytes or several gigabytes of voxel data which needs to be converted to a format that can be streamed to the viewer, and rendered in real-time.
  • the amount of data depends on the world complexity and volume. The larger impact comes in a multi-device recording setup with a number of separate locations where the cameras are recording. Such a setup produces more information than a camera at a single location.
  • Fig. 1 shows a system for capturing, encoding, decoding, reconstructing and viewing a three-dimensional scheme, that is, for 3D video and 3D audio digital creation and playback.
  • the task of the system is that of capturing sufficient visual and auditory information from a specific scene to be able to create a scene model such that a convincing reproduction of the experience, or presence, of being in that location can be achieved by one or more viewers physically located in different locations and optionally at a time later in the future.
  • Such reproduction requires more information that can be captured by a single camera or microphone, in order that a viewer can determine the distance and location of objects within the scene using their eyes and their ears.
  • two camera sources are used.
  • the human auditory system can be able to sense the direction of sound, at least two microphones are used (the commonly known stereo sound is created by recording two audio channels).
  • the human auditory system can detect the cues, e.g. in timing difference of the audio signals to detect the direction of sound.
  • the system of Fig. 1 may consist of three main parts: image sources, a server and a rendering device.
  • a video source SRC1 may comprise multiple cameras CAM1, CAM2, .. CAMN with overlapping field of view so that regions of the view around the video capture device is captured from at least two cameras.
  • the video source SRC1 may comprise multiple microphones to capture the timing and phase differences of audio originating from different directions.
  • the video source SRC1 may comprise a high- resolution orientation sensor so that the orientation (direction of view) of the plurality of cameras CAM1, CAM2, ..., CAMN can be detected and recorded.
  • the cameras or the computers may also comprise or be functionally connected to means for forming distance information corresponding to the captured images, for example so that the pixels have corresponding depth data.
  • Such depth data may be formed by scanning the depth or it may be computed from the different images captured by the cameras.
  • the video source SRC1 comprises or is functionally connected to, or each of the plurality of cameras CAM1, CAM2, ..., CAMN comprises or is functionally connected to a computer processor and memory, the memory comprising computer program code for controlling the source and/or the plurality of cameras.
  • the image stream captured by the video source i.e. the plurality of the cameras, may be stored on a memory device for use in another device, e.g. a viewer, and/or transmitted to a server using a communication interface. It needs to be understood that although a video source comprising three cameras is described here as part of the system, another amount of camera devices may be used instead as part of the system.
  • one or more sources SRC2 of synthetic imagery may be present in the system, comprising a scene model. Such sources may be used to create and transmit the scene model and its development over time, e.g. instantaneous states of the model.
  • the model can be created or provided by the source SRC1 and/or SRC2, or by the server SERVER. Such sources may also use the model of the scene to compute various video bitstreams for transmission.
  • One or more two-dimensional video bitstreams may be computed at the server SERVER or a device RENDERER used for rendering, or another device at the receiving end.
  • the devices SRC1 and SRC2 may comprise or be functionally connected to one or more computer processors (PROC2 shown) and memory (MEM2 shown), the memory comprising computer program (PROGR2 shown) code for controlling the source device SRC1/SRC2.
  • the image stream captured by the device and the scene model may be stored on a memory device for use in another device, e.g. a viewer, or transmitted to a server or the viewer using a
  • the communication interface COMM2 There may be a storage, processing and data stream serving network in addition to the capture device SRC1.
  • a server SERVER or a plurality of servers storing the output from the capture device SRC1 or device SRC2 and/or to form a scene model from the data from devices SRC1, SRC2.
  • the device SERVER comprises or is functionally connected to a computer processor PROC3 and memory MEM3, the memory comprising computer program PROGR3 code for controlling the server.
  • the device SERVER may be connected by a wired or wireless network connection, or both, to sources SRC1 and/or SRC2, as well as the viewer devices VIEWER1 and VIEWER2 over the communication interface COMM3.
  • the creation of a three-dimensional scene model may take place at the server SERVER or another device by using the images captured by the devices SRC1.
  • the scene model may be a model created from captured image data (a real-world model), or a synthetic model such as on device SRC2, or a combination of such.
  • the scene model may be encoded to reduce its size and transmitted to a decoder, for example viewer devices.
  • the viewer devices may have a rendering module and a display module, or these functionalities may be combined in a single device.
  • the devices may comprise or be functionally connected to a computer processor PROC4 and memory MEM4, the memory comprising computer program PROG4 code for controlling the viewing devices.
  • the viewer (playback) devices may consist of a data stream receiver for receiving a video data stream and for decoding the video data stream.
  • the video data stream may be received from the server SERVER or from some other entity, such as a proxy server, an edge server of a content delivery network, or a file available locally in the viewer device.
  • the data stream may be received over a network connection through communications interface COMM4, or from a memory device MEM6 like a memory card CARD2.
  • the viewer devices may have a graphics processing unit for processing of the data to a suitable format for viewing.
  • the viewer VIEWER1 may comprise a high- resolution stereo-image head-mounted display for viewing the rendered stereo video sequence.
  • the head-mounted display may have an orientation sensor DET1 and stereo audio headphones.
  • the viewer VIEWER2 may comprise a display (either two-dimensional or a display enabled with 3D technology for displaying stereo video), and the rendering device may have an orientation detector DET2 connected to it.
  • the viewer VIEWER2 may comprise a 2D display, since the volumetric video rendering can be done in 2D by rendering the viewpoint from a single eye instead of a stereo eye pair.
  • Fig. 1 depicts one SRC1 device and one SRC2 device, but generally the system may comprise more than one SRC1 device and/or SRC2 device.
  • VIEWER2 may be a computer or a portable computing device, or be connected to such or configured to be connected to such. Moreover, even if the devices (SRC1, SRC2,
  • SERVER, RENDERER, VIEWER1, VIEWER2) are depicted as a single device in Fig. 1, they may comprise multiple parts or may be comprised of multiple connected devices.
  • SERVER may comprise several devices, some of which may be used for editing the content produced by SRC1 and/or SRC2 devices, some others for compressing the edited content, and a third set of devices may be used for transmitting the compressed content.
  • Such devices may have computer program code for carrying out methods according to various examples described in this text.
  • Figs. 2a and 2b show a capture device and a viewing device, respectively.
  • the camera has a camera detector CAMDET1, comprising a plurality of sensor elements for sensing intensity of the light hitting the sensor element.
  • the camera has a lens OBJ1 (or a lens arrangement of a plurality of lenses), the lens being positioned so that the light hitting the sensor elements travels through the lens to the sensor elements.
  • the camera detector CAMDET1 has a nominal centre point CP1 that is a middle point of the plurality of sensor elements, for example for a rectangular sensor the crossing point of diagonals of the rectangular sensor.
  • the lens has a nominal centre point PP1, as well, lying for example on the axis of symmetry of the lens.
  • the direction of orientation of the camera is defined by the line passing through the centre point CP1 of the camera sensor and the centre point PP1 of the lens.
  • the direction of the camera is a vector along this line pointing in the direction from the camera sensor to the lens.
  • the optical axis of the camera is understood to be this line CP1-PP1.
  • the optical path from the lens to the camera detector need not always be a straight line but there may be mirrors and/or some other elements which may affect the optical path between the lens and the camera detector.
  • Fig. 2b shows a head-mounted display (HMD) for stereo viewing.
  • the head- mounted display comprises two screen sections or two screens DISP1 and DISP2 for displaying the left and right eye images.
  • the displays are close to the eyes, and therefore lenses are used to make the images easily viewable and for spreading the images to cover as much as possible of the eyes' field of view.
  • the device When the device will be used by a user, the user may put the device on her/his head so that it will be attached to the head of the user so that it stays in place even when the user turns his head.
  • the device may have an orientation detecting module ORDET1 for determining the head movements and direction of the head.
  • the head-mounted display gives a three-dimensional (3D) perception of the
  • Time-synchronized video and orientation data is first recorded with the capture devices. This can consist of multiple concurrent video streams as described above.
  • One or more time-synchronized audio streams may also be recorded with the capture devices.
  • the different capture devices may form image and geometry information of the scene from different directions. For example, there may be three, four, five, six or more cameras capturing the scene from different sides, like front, back, left and right, and/or at directions between these, as well as from the top or bottom, or any combination of these.
  • the cameras may be at different distances, for example some of the cameras may capture the whole scene and some of the cameras may be capturing one or more objects in the scene.
  • the cameras or the system may comprise means for determining geometry information, e.g. depth data, related to the captured video streams. From these concurrent video and audio streams, a computer model of a scene may be created. Alternatively or additionally, a synthetic computer model of a virtual scene may be used. The models (at successive time instances) are then transmitted immediately or later to the storage and processing network for processing and conversion into a format suitable for subsequent delivery to playback devices.
  • geometry information e.g. depth data
  • the conversion may involve processing and coding to improve the quality and/or reduce the quantity of the scene model data while preserving the quality at a desired level.
  • Each playback device receives a stream of the data (either computed video data or scene model data) from the network, and renders it into a viewing reproduction of the original location which can be experienced by a user.
  • the reproduction may be two-dimensional or three-dimensional (stereo image pairs).
  • Figs. 3a and 3b show an encoder and decoder for encoding and decoding texture pictures, geometry pictures and/or auxiliary pictures.
  • a video codec consists of an encoder that transforms an input video into a compressed representation suited for
  • the encoder discards and/or loses some information in the original video sequence in order to represent the video in a more compact form (that is, at lower bitrate).
  • An example of an encoding process is illustrated in Figure 3a.
  • Figure 3a illustrates an image to be encoded (F); a predicted representation of an image block (P' n ); a prediction error signal (D n ); a reconstructed prediction error signal (D' n ); a preliminary reconstructed image (I' n ); a final reconstructed image (R' n ); a transform (T) and inverse transform (T -1 ); a quantization (Q) and inverse quantization (Q 1 ); entropy encoding (E); a reference frame memory (RFM); inter prediction (Pi nter ); intra prediction (Pi ntra ); mode selection (MS) and filtering (F).
  • Figure 3b illustrates a predicted representation of an image block (P' n ); a reconstructed prediction error signal (D' n ); a preliminary reconstructed image (I' n ); a final reconstructed image (R' n ); an inverse transform (T 1 ); an inverse quantization (Q 1 ); an entropy decoding (E 1 ); a reference frame memory (RFM); a prediction (either inter or intra) (P); and filtering (F).
  • pixel values in a certain picture area are predicted for example by motion compensation means (finding and indicating an area in one of the previously coded video frames that corresponds closely to the block being coded) or by spatial means (using the pixel values around the block to be coded in a specified manner).
  • the prediction error i.e. the difference between the predicted block of pixels and the original block of pixels. This is typically done by transforming the difference in pixel values using a specified transform (e.g. Discrete Cosine Transform (DCT) or a variant of it), quantizing the coefficients and entropy coding the quantized coefficients.
  • DCT Discrete Cosine Transform
  • Video codecs may also provide a transform skip mode, which the encoders may choose to use.
  • the prediction error is coded in a sample domain, for example by deriving a sample-wise difference value relative to certain adjacent samples and coding the sample-wise difference value with an entropy coder.
  • HEVC High Efficiency Video Coding
  • a coding block may be defined as an NxN block of samples for some value of N such that the division of a coding tree block into coding blocks is a partitioning.
  • a coding tree block may be defined as an NxN block of samples for some value of N such that the division of a component into coding tree blocks is a partitioning.
  • a coding tree unit may be defined as a coding tree block of luma samples, two corresponding coding tree blocks of chroma samples of a picture that has three sample arrays, or a coding tree block of samples of a monochrome picture or a picture that is coded using three separate color planes and syntax structures used to code the samples.
  • a coding unit may be defined as a coding block of luma samples, two corresponding coding blocks of chroma samples of a picture that has three sample arrays, or a coding block of samples of a monochrome picture or a picture that is coded using three separate color planes and syntax structures used to code the samples.
  • a CU with the maximum allowed size may be named as LCU (largest coding unit) or coding tree unit (CTU) and the video picture is divided into non-overlapping LCUs.
  • a picture can be partitioned in tiles, which are rectangular and contain an integer number of LCUs.
  • the partitioning to tiles forms a regular grid, where heights and widths of tiles differ from each other by one LCU at the maximum.
  • a slice is defined to be an integer number of coding tree units contained in one independent slice segment and all subsequent dependent slice segments (if any) that precede the next independent slice segment (if any) within the same access unit.
  • a slice segment is defined to be an integer number of coding tree units ordered consecutively in the tile scan and contained in a single NAL unit. The division of each picture into slice segments is a partitioning.
  • an independent slice segment is defined to be a slice segment for which the values of the syntax elements of the slice segment header are not inferred from the values for a preceding slice segment
  • a dependent slice segment is defined to be a slice segment for which the values of some syntax elements of the slice segment header are inferred from the values for the preceding independent slice segment in decoding order.
  • a slice header is defined to be the slice segment header of the independent slice segment that is a current slice segment or is the independent slice segment that precedes a current dependent slice segment
  • a slice segment header is defined to be a part of a coded slice segment containing the data elements pertaining to the first or all coding tree units represented in the slice segment.
  • the CUs are scanned in the raster scan order of LCUs within tiles or within a picture, if tiles are not in use. Within an LCU, the CUs have a specific scan order.
  • Entropy coding/decoding may be performed in many ways. For example, context-based coding/decoding may be applied, where in both the encoder and the decoder modify the context state of a coding parameter based on previously coded/decoded coding parameters.
  • Context-based coding may for example be context adaptive binary arithmetic coding (CABAC) or context-based variable length coding (CAVLC) or any similar entropy coding.
  • Entropy coding/decoding may alternatively or additionally be performed using a variable length coding scheme, such as Huffman coding/decoding or Exp-Golomb coding/decoding. Decoding of coding parameters from an entropy-coded bitstream or codewords may be referred to as parsing.
  • Available media file format standards include ISO base media file format (ISO/IEC 14496-12, which may be abbreviated ISOBMFF).
  • ISOBMFF ISO base media file format
  • HEIF High Efficiency Image File Format
  • Out-of-band transmission, signaling or storage can be used for tolerance against transmission errors as well as for other purposes, such as ease of access or session negotiation.
  • a sample entry of a track in a file conforming to the ISO Base Media File Format may comprise parameter sets, while the coded data in the bitstream is stored elsewhere in the file or in another file.
  • the phrase along the bitstream e.g.
  • indicating along the bitstream or along a coded unit of a bitstream (e.g. indicating along a coded tile) may be used in claims and described embodiments to refer to out-of-band transmission, signaling, or storage in a manner that the out-of-band data is associated with the bitstream or the coded unit, respectively.
  • decoding along the bitstream or along a coded unit of a bitstream or alike may refer to decoding the referred out-of-band data (which may be obtained from out-of-band transmission, signaling, or storage) that is associated with the bitstream or the coded unit, respectively.
  • the phrase along the bitstream may be used when the bitstream is contained in a file, such as a file conforming to the ISO Base Media File Format, and certain file metadata is stored in the file in a manner that associates the metadata to the bitstream, such as boxes in the sample entry for a track containing the bitstream, a sample group for the track containing the bitstream, or a timed metadata track associated with the track containing the bitstream.
  • a file such as a file conforming to the ISO Base Media File Format
  • certain file metadata is stored in the file in a manner that associates the metadata to the bitstream, such as boxes in the sample entry for a track containing the bitstream, a sample group for the track containing the bitstream, or a timed metadata track associated with the track containing the bitstream.
  • ISOBMFF Some concepts, structures, and specifications of ISOBMFF are described below as an example of a container file format, based on which the embodiments may be implemented.
  • the aspects of the invention are not limited to ISOBMFF, but rather the description is given for one possible basis on top of which the invention may be partly or fully realized.
  • a basic building block in the ISO base media file format is called a box.
  • Each box has a header and a payload.
  • the box header indicates the type of the box and the size of the box in terms of bytes.
  • a box may enclose other boxes, and the ISO file format specifies which box types are allowed within a box of a certain type. Furthermore, the presence of some boxes may be mandatory in each file, while the presence of other boxes may be optional. Additionally, for some box types, it may be allowable to have more than one box present in a file. Thus, the ISO base media file format may be considered to specify a hierarchical structure of boxes.
  • a file includes media data and metadata that are encapsulated into boxes. Each box is identified by a four character code (4CC) and starts with a header which informs about the type and size of the box.
  • 4CC four character code
  • the media data may be provided in a media data‘mdat’ box and the movie‘moov’ box may be used to enclose the metadata.
  • both of the‘mdat’ and‘moov’ boxes may be required to be present.
  • the movie‘moov’ box may include one or more tracks, and each track may reside in one corresponding track‘trak’ box.
  • a track may be one of the many types, including a media track that refers to samples formatted according to a media compression format (and its encapsulation to the ISO base media file format).
  • the Matroska file format is capable of (but not limited to) storing any of video, audio, picture, or subtitle tracks in one file.
  • Matroska may be used as a basis format for derived file formats, such as WebM.
  • Matroska uses Extensible Binary Meta Language (EBML) as basis.
  • EBML specifies a binary and octet (byte) aligned format inspired by the principle of XML.
  • EBML itself is a generalized description of the technique of binary markup.
  • a Matroska file consists of Elements that make up an EBML "document.” Elements incorporate an Element ID, a descriptor for the size of the element, and the binary data itself. Elements can be nested.
  • a Segment Element of Matroska is a container for other top-level (level 1) elements.
  • a Matroska file may comprise (but is not limited to be composed of) one Segment.
  • Multimedia data in Matroska files is organized in Clusters (or Cluster Elements), each containing typically a few seconds of multimedia data.
  • a Cluster comprises BlockGroup elements, which in turn comprise Block Elements.
  • a Cues Element comprises metadata which may assist in random access or seeking and may include file pointers or respective timestamps for seek points.
  • Figs. 4a, 4b, 4c and 4d show a setup for forming a stereo image of a scene to a user, for example a video frame of a 3D video.
  • Fig. 4a a situation is shown where a human being is viewing two spheres Al and A2 using both eyes El and E2.
  • the sphere Al is closer to the viewer than the sphere A2, the respective distances to the first eye El being LEI,AI and LEI,A2.
  • the different objects reside in space at their respective (x,y,z) coordinates, defined by the coordinate system SZ, SY and SZ.
  • the distance di 2 between the eyes of a human being may be approximately 62-64 mm on average, and varying from person to person between 55 and 74 mm. This distance is referred to as the parallax, on which stereoscopic view of the human vision is based on.
  • the viewing directions (optical axes) DIR1 and DIR2 are typically essentially parallel, possibly having a small deviation from being parallel, and define the field of view for the eyes.
  • the head of the user has an orientation (head orientation) in relation to the surroundings, most easily defined by the common direction of the eyes when the eyes are looking straight ahead. That is, the head orientation tells the yaw, pitch and roll of the head in respect of a coordinate system of the scene where the user is.
  • the spheres Al and A2 are in the field of view of both eyes.
  • the centre-point O12 between the eyes and the spheres are on the same line. That is, from the centre-point, the sphere A2 is behind the sphere Al .
  • each eye sees part of sphere A2 from behind Al, because the spheres are not on the same line of view from either of the eyes.
  • Fig. 4b there is a setup shown, where the eyes have been replaced by cameras Cl and C2, positioned at the location where the eyes were in Fig. 4a.
  • the distances and directions of the setup are otherwise the same.
  • the 4b is to be able to take a stereo image of the spheres Al and A2.
  • the two images resulting from image capture are Fci and Fc2.
  • the "left eye” image Fci shows the image S A 2 of the sphere A2 partly visible on the left side of the image SAI of the sphere Al .
  • the "right eye” image Fc2 shows the image S A 2 of the sphere A2 partly visible on the right side of the image SAI of the sphere Al .
  • This difference between the right and left images is called disparity, and this disparity, being the basic mechanism with which the HVS determines depth information and creates a 3D view of the scene, can be used to create an illusion of a 3D image.
  • the camera pair Cl and C2 has a natural parallax, that is, it has the property of creating natural disparity in the two images of the cameras. Natural disparity may be understood to be created even though the distance between the two cameras forming the stereo camera pair is somewhat smaller or larger than the normal distance (parallax) between the human eyes, e.g. essentially between 40 mm and 100 mm or even 30 mm and 120 mm.
  • the images Fci and Fc 2 may be captured by cameras Cl and C2, where the cameras Cl and C2 may be real-world cameras or they may be virtual cameras.
  • the images Fci and Fc 2 may be computed from a computer model of a scene by setting the direction, orientation and viewport of the cameras Cl and C2 appropriately such that a stereo image pair suitable for viewing by the human visual system (HVS) is created.
  • HVS human visual system
  • Fig. 4c the creating of this 3D illusion is shown.
  • the images Fci and Fc 2 captured or computed by the cameras Cl and C2 are displayed to the eyes El and E2, using displays Dl and D2, respectively.
  • the disparity between the images is processed by the human visual system so that an understanding of depth is created. That is, when the left eye sees the image S A 2 of the sphere A2 on the left side of the image S AI of sphere Al, and respectively the right eye sees the image S A 2 of the sphere A2 on the right side, the human visual system creates an understanding that there is a sphere V2 behind the sphere VI in a three-dimensional world.
  • the images Fci and Fc 2 can also be synthetic, that is, created by a computer. If they carry the disparity information, synthetic images will also be seen as three-dimensional by the human visual system. That is, a pair of computer-generated images can be formed so that they can be used as a stereo image.
  • Fig. 4d illustrates how the principle of displaying stereo images to the eyes can be used to create 3D movies or virtual reality scenes having an illusion of being three- dimensional.
  • the images Fxi and Fx2 are either captured with a stereo camera or computed from a model so that the images have the appropriate disparity.
  • a large number e.g. 30
  • the human visual system will create a cognition of a moving, three-dimensional image.
  • the field of view represented by the content may be greater than the displayed field of view e.g. in an arrangement depicted in Fig. 4d. Consequently, only a part of the content along the direction of view (a.k.a. viewing orientation) is displayed at a single time.
  • This direction of view that is, the head orientation
  • This direction of view may be determined as a real orientation of the head e.g. by an orientation detector mounted on the head, or as a virtual orientation determined by a control device such as a joystick or mouse that can be used to manipulate the direction of view without the user actually moving his head.
  • head orientation may be used to refer to the actual, physical orientation of the user's head and changes in the same, or it may be used to refer to the virtual direction of the user's view that is determined by a computer program or a computer input device.
  • the content may enable viewing from several viewing positions within the 3D space.
  • the texture picture(s), the geometry picture(s) and the geometry information may be used to synthesize the images Fxi and/or Fx 2 as if the displayed content was captured by camera(s) located at the viewing position.
  • volumetric video describes a 3D scene or object at different (successive) time instances, such data can be viewed from any viewpoint. Therefore, volumetric video is an important format for any augmented reality, virtual reality and mixed reality applications, especially for providing viewing capabilities having six degrees of freedom (so-called 6DOF viewing).
  • FIG. 5a illustrates projection of source volumes in a digital scene model SCE and parts of an object model OBJ1, OBJ2, OBJ3, BG4 to projection surfaces Sl, S2, S3,
  • the projection of source volumes SV1, SV2, SV3, SV4 may result in texture pictures and geometry pictures, and there may be geometry information related to the projection source volumes and/or projection surfaces.
  • Texture pictures, geometry pictures and projection geometry information may be encoded into a bitstream.
  • a texture picture may comprise information on the colour data of the source of the projection. Through the projection, such colour data may result in pixel colour information in the texture picture. Pixels may be coded in groups, e.g. coding units of rectangular shape.
  • the projection geometry information may comprise but is not limited to one or more of the following:
  • projection surface type such as a cube, sphere, cylinder, polyhedron - location of the projection surface in 3D space
  • a projection centre such as a projection centre point, axis, or plane, from which a geometry primitive is projected onto the projection surface
  • the projection may take place by projecting the geometry primitives (points of a point could, triangles of a triangle mesh or voxels of a voxel array) of a source volume SV1, SV2, SV3, SV4 (or an object OBJ1, OBJ2, OBJ3, BG4) onto a projection surface Sl, S2, S3, S4.
  • the geometry primitives may comprise information on the texture, for example a colour value or values of a point, a triangle or a voxel.
  • the projection surface may surround the source volume at least partially such that projection of the geometry primitives happens from the centre of the projection surface outwards to the surface.
  • a cylindrical surface has a projection centre axis and a spherical surface has a projection centre point.
  • a cubical or rectangular surface may have projection centre planes or a projection centre axis or point and the projection of the geometry primitives may take place either orthogonally to the sides of the surface or from the projection centre axis or point outwards to the surface.
  • the projection surfaces e.g. cylindrical and rectangular, may be open from the top and the bottom such that when the surface is cut and rolled out on a two-dimensional plane, it forms a rectangular shape.
  • Such rectangular shape with pixel data can be encoded and decoded with a video codec.
  • the projection surface such as a planar surface or a sphere may be inside group of geometry primitives, e.g. inside a point cloud that defines a surface.
  • the projection may take place from outside in towards the centre and may result in sub-sampling of the texture data of the source.
  • points may be represented with any floating point coordinates.
  • a quantized point cloud may be used to reduce the amount of data, whereby the coordinate values of the point cloud are represented e.g. with lO-bit, 12-bit or 16-bit integers. Integers may be used because hardware accelerators may be able to operate on integers more efficiently.
  • the points in the point cloud may have associated colour, reflectance, opacity etc. texture values.
  • the points in the point cloud may also have a size, or a size may be the same for all points. The size of the points may be understood as indicating how large an object the point appears to be in the model in the projection.
  • the point cloud is projected by ray casting from the projection surface to find out the pixel values of the projection surface. In such a manner, the topmost point remains visible in the projection, while points closer to the centre of the projection surface may be occluded.
  • the original point cloud, meshes, voxels, or any other model is projected outwards to a simple geometrical shape, this simple geometrical shape being the projection surface.
  • Different projection surfaces may have different characteristics in terms of projection and reconstruction.
  • a projection to a cubical surface may be the most efficient, and a cylindrical projection surface may provide accurate results efficiently.
  • cones, polyhedron-based parallelepipeds (hexagonal or octagonal, for example) and spheres or a simple plane may be used as projection surfaces.
  • the phrase along the bitstream may be defined to refer to out-of-band transmission, signalling, or storage in a manner that the out- of-band data is associated with the bitstream.
  • the phrase decoding along the bitstream or alike may refer to decoding the referred out-of-band data (which may be obtained from out-of-band transmission, signalling, or storage) that is associated with the bitstream.
  • an indication along the bitstream may refer to metadata in a container file that encapsulates the bitstream.
  • a first texture picture may be encoded into a bitstream, and the first texture picture may comprise a first projection of texture data of a first source volume SV1 of a scene model SCE onto a first projection surface Sl.
  • the scene model SCE may comprise a number of further source volumes SV2, SV3, SV4.
  • data on the position of the originating geometry primitive may also be determined, and based on this determination, a geometry picture may be formed. This may happen for example so that depth data is determined for each or some of the texture pixels of the texture picture. Depth data is formed such that the distance from the originating geometry primitive such as a point to the projection surface is determined for the pixels. Such depth data may be represented as a depth picture, and similarly to the texture picture, such geometry picture (in this example, depth picture) may be encoded and decoded with a video codec.
  • This first geometry picture may be seen to represent a mapping of the first projection surface to the first source volume, and the decoder may use this information to determine the location of geometry primitives in the model to be reconstructed.
  • a picture may be defined to be either a frame or a field.
  • a frame may be defined to comprise a matrix of luma samples and possibly the corresponding chroma samples.
  • a field may be defined to be a set of alternate sample rows of a frame. Fields may be used as encoder input for example when the source signal is interlaced. Chroma sample arrays may be absent (and hence monochrome sampling may be in use) or may be subsampled when compared to luma sample arrays.
  • each of the two chroma arrays has half the height and half the width of the luma array.
  • each of the two chroma arrays has the same height and half the width of the luma array.
  • each of the two chroma arrays has the same height and width as the luma array.
  • An attribute picture may be defined as a picture that comprises additional information related to an associated texture picture.
  • An attribute picture may for example comprise surface normal, opacity, or reflectance information for a texture picture.
  • a geometry picture may be regarded as one type of an attribute picture, although a geometry picture may be treated as its own picture type, separate from an attribute picture.
  • Texture picture(s) and the respective geometry picture(s), if any, and the respective attribute picture(s) may have the same or different chroma format.
  • Terms texture image and texture picture may be used interchangeably.
  • Terms geometry image and geometry picture may be used interchangeably.
  • a specific type of a geometry image is a depth image.
  • Embodiments described in relation to a geometry image equally apply to a depth image, and embodiments described in relation to a depth image equally apply to a geometry image.
  • Terms attribute image and attribute picture may be used interchangeably.
  • a geometry picture and/or an attribute picture may be treated as an auxiliary picture in video/image encoding and/or decoding.
  • a pixel may be defined to a be a sample of one of the sample arrays of the picture or may be defined to comprise the collocated samples of all the sample arrays of the picture.
  • multiple source volumes may be encoded as texture pictures, geometry pictures and projection geometry information into the bitstream in a similar manner. That is, as in Fig. 5a, the scene model SCE may comprise multiple objects OBJ1, OBJ2, OBJ3, OBJ4, and these may be treated as source volumes SV1, SV2, SV3, SV4 and each object may be coded as a texture picture, geometry picture and projection geometry information.
  • the first texture picture of the first source volume SV1 and further texture pictures of the other source volumes SV2, SV3, SV4 may represent the same time instance. That is, there may be a plurality of texture and geometry pictures and projection geometry information for one time instance, and the other time instances may be coded in a similar manner. Since the various source volumes are in this way producing sequences of texture pictures and sequences of geometry pictures, as well as sequences of projection geometry information, the inter-picture redundancy in the picture sequences can be used to encode the texture and geometry data for the source volumes efficiently, compared to the presently known ways of encoding volume data.
  • An object OBJ3 (source volume SV3) may be projected onto a projection surface S3 and encoded into the bitstream as a texture picture, geometry picture and projection geometry information as described above. Furthermore, such source volume may be indicated to be static by encoding information into said bitstream on said fourth projection geometry being static.
  • a static source volume or object may be understood to be an object whose position with respect to the scene model remains the same over two or more or all time instances of the video sequence.
  • the geometry data may also stay the same, that is, the object's shape remains the same over two or more time instances.
  • some or all of the texture data may stay the same over two or more time instances.
  • the decoder By encoding information into the bitstream of the static nature of the source volume the encoding efficiency may further be improved, as the same information may not need to be coded multiple times. In this manner, the decoder will also be able to use the same reconstruction or partially same reconstruction of the source volume (object) over multiple time instances.
  • the different source volumes may be coded into the bitstream with different frame rates.
  • a slow-moving or relatively unchanging object may be encoded with a first frame rate
  • a fast-moving and/or changing object may be coded with a second frame rate.
  • the first frame rate may be slower than the second frame rate, for example one half or one quarter of the second frame rate, or even slower.
  • the second frame rate may be 15 frames per second, or 1 frame per second.
  • the first and second object (source volumes) may be "sampled" in synchrony such that some frames of the faster frame rate coincide with frames of the slower frame rate.
  • the scene model may have a coordinate system and one or more of the objects (source volumes) in the scene model may have their local coordinate systems.
  • the shape, size, location and orientation of one or more projection surfaces may be encoded into or along the bitstream with respect to the scene model coordinates.
  • the encoding may be done with respect to coordinates of the scene model or said first source volume. The choice of coordinate systems may improve the coding efficiency.
  • Information on temporal changes in location, orientation and size of one or more said projection surfaces may be encoded into or along the bitstream. For example, if one or more of the objects (source volumes) being encoded is moving or rotating with respect to the scene model, the projection surface moves or rotates with the object to preserve the projection as similar as possible. [0100] If the projection volumes are changing, for example splitting or bending into two parts, the projection surfaces may be sub-divided respectively. Therefore, information on sub-division of one or more of the source volumes and respective changes in one or more of the projection surfaces may be encoded into or along the bitstream.
  • the resulting bitstream may then be output to be stored or transmitted for later decoding and reconstruction of the scene model.
  • a first texture picture may be decoded from a bitstream to obtain first decoded texture data, where the first texture picture comprises a first projection of texture data of a first source volume of the scene model to be reconstructed onto a first projection surface.
  • the scene model may comprise a number of further source volumes.
  • a first geometry picture may be decoded from the bitstream to obtain first decoded scene model geometry data.
  • the first geometry picture may represent a mapping of the first projection surface to the first source volume.
  • First projection geometry information of the first projection may be decoded from the bitstream, the first projection geometry information comprising information of position of the first projection surface in the scene model.
  • a reconstructed scene model may be formed by projecting the first decoded texture data to a first destination volume using the first decoded scene model geometry data and said first projection geometry information to determine where the decoded texture information is to be placed in the scene model.
  • a 3D scene model may be classified into two parts: first all dynamic parts, and second all static parts.
  • the dynamic part of the 3D scene model may further be sub-divided into separate parts, each representing objects (or parts of) an object in the scene model, that is, source volumes.
  • the static parts of the scene model may include e.g. static room geometry (walls, ceiling, fixed furniture) and may be compressed either by known volumetric data compression solutions, or, similar to the dynamic part, sub-divided into individual objects for projection-based compression as described earlier, to be encoded into the bitstream.
  • some objects may be a chair (static), a television screen (static geometry, dynamic texture), a moving person (dynamic).
  • a suitable projection geometry surface
  • cube projection to represent the chair
  • another cube for the screen e.g. a cylinder for the person's torso
  • a sphere for a detailed representation of the person's head e.g. a chair with a cylinder with a cylinder with a sphere with a detailed representation of the person's head, and so on.
  • the 3D data of each object may then be projected onto the respective projection surface and 2D planes are derived by "unfolding" the projections from three dimensions to two dimensions (plane).
  • the unfolded planes will have several channels, typically three for the colour representation of the texture, e.g.
  • RGB RGB, YUV, and one additional plane for the geometry (depth) of each projected point for later reconstruction.
  • Frame packing may be defined to comprise arranging more than one input picture, which may be referred to as (input) constituent frames, into an output picture.
  • frame packing is not limited to any particular type of constituent frames or the constituent frames need not have a particular relation with each other.
  • frame packing is used for arranging constituent frames of a stereoscopic video clip into a single picture sequence.
  • the arranging may include placing the input pictures in spatially non-overlapping areas within the output picture. For example, in a side-by-side
  • the arranging may also include partitioning of one or more input pictures into two or more constituent frame partitions and placing the constituent frame partitions in spatially non-overlapping areas within the output picture.
  • the output picture or a sequence of frame-packed output pictures may be encoded into a bitstream e.g. by a video encoder.
  • the bitstream may be decoded e.g. by a video decoder.
  • the decoder or a post-processing operation after decoding may extract the decoded constituent frames from the decoded picture(s) e.g. for displaying.
  • a standard 2D video encoder may then receive the planes as inputs, either as individual layers per object, or as a frame-packed representation of all objects.
  • the texture picture may thus comprise a plurality of projections of texture data from further source volumes and the geometry picture may represent a plurality of mappings of projection surfaces to the source volume.
  • separation boundaries may be signalled to recreate the individual planes for each object
  • separation boundaries may be signalled to recreate the individual planes for each object
  • classification of each object as static/dynamic may be signalled
  • geometry channel(s) e.g. quantisation method, depth ranges, bit depth, etc. may be signalled
  • the decoder may receive the static 3D scene model data together with the video bitstreams representing the dynamic parts of the scene model. Based on the signalled information on the projection geometries, each object may be reconstructed in 3D space and the decoded scene model is created by fusing all reconstructed parts (objects or source volumes) together.
  • Standard video encoding hardware may be utilized for real-time
  • Depth may be coded "outside-in” (indicating the distance from the projection surface to the 3D point), or "inside-out” (indicating the distance from the 3D point to the projection surface). In inside-out coding, depth of each projected point may be positive (with positive distance PD1) or negative (with negative distance).
  • Fig. 5b shows an example of projecting an object OBJ1 using a cube map projection format, wherein there are six proj ection surfaces PS 1 , ... ,PS6 of the proj ection cube PC 1.
  • the projection surfaces are one on the left side PS1, one in front PS2, one on the right side PS3, one in the back PS4, one in the bottom PS5, and one in the top PS6 of the cube PC1 in the setup of Figure 5b.
  • the projection surfaces on the left PS1, on the right PS3, in the front PS2 and at in the back PS4 are shown. It is, however, clear to a skilled person to utilize similar principles on all six projection surfaces when the cube map projection format is used.
  • Fig. 6 shows a projection of a source volume to a projection surface, and inpainting of a sparse projection.
  • a three-dimensional (3D) scene model represented as objects OBJ1 comprising geometry primitives such as mesh elements, points, and/or voxel, may be projected onto one, or more, projection surfaces, as described earlier.
  • these projection surface geometries may be "unfolded" onto 2D planes (two planes per projected source volume: one for texture TP1, one for depth GP1), which may then be encoded using standard 2D video compression technologies.
  • Relevant projection geometry information may be transmitted alongside the encoded video files to the decoder.
  • the decoder may then decode the video and performs the inverse projection to regenerate the 3D scene model object ROBJ1 in any desired representation format, which may be different from the starting format e.g. reconstructing a point cloud from original mesh model data.
  • auxiliary pictures related to one or more said texture pictures and the pixels thereof may be encoded into or along with the bitstream.
  • the auxiliary pictures may e.g. represent texture surface properties related to one or more of the source volumes. Such texture surface properties may be e.g. surface normal information (e.g. with respect to the projection direction), reflectance and opacity (e.g. an alpha channel value).
  • An encoder may encode, in or along with the bitstream, indication(s) of the type(s) of texture surface properties represented by the auxiliary pictures, and a decoder may decode, from or along the bitstream, indication(s) of the type(s) of texture surface properties represented by the auxiliary pictures.
  • Mechanisms to represent an auxiliary picture may include but are not limited to the following:
  • a colour component sample array such as a chroma sample array, of the geometry picture.
  • An additional sample array in addition to the conventional three colour component sample arrays of the texture picture or the geometry picture.
  • a constituent frame of a frame-packed picture that may also comprise texture picture(s) and/or geometry picture(s).
  • auxiliary picture included in specific data units in the bitstream.
  • H.264/AVC Advanced Video Coding
  • NAL network abstraction layer
  • An auxiliary picture layer within a layered bitstream comprises the feature of including auxiliary picture layers in the bitstream.
  • An auxiliary picture layer comprises auxiliary pictures.
  • auxiliary picture bitstream separate from the bitstream(s) for the texture picture(s) and geometry picture(s).
  • the auxiliary picture bitstream may be indicated, for example in a container file, to be associated with the bitstream(s) for the texture pictures(s) and geometry picture(s).
  • the mechanism(s) to be used for auxiliary pictures may be pre-defined e.g. in a coding standard, or the mechanism(s) may be selected e.g. by an encoder and indicated in or along the bitstream.
  • the decoder may decode the mechanism(s) used for auxiliary pictures from or along the bitstream.
  • the projection surface of a source volume may encompass the source volume, and there may be a model of an object in that source volume. Encompassing may be understood so that the object (model) is inside the surface such that when looking from the centre axis or centre point of the surface, the object's points are closer to the centre than the points of the projection surface are.
  • the model may be made of geometry primitives, as described.
  • the geometry primitives of the model may be projected onto the projection surface to obtain projected pixels of the texture picture. This projection may happen from inside-out. Alternatively or in addition, the projection may happen from outside-in.
  • Projecting 3D data onto 2D planes is independent from the 3D scene model representation format.
  • Figure 7 illustrates an example of this kind of situation.
  • the person’s left hand occludes a part of the body of the person so that when viewed
  • the 3D volume surface is analysed with respect to the target projection surface before performing the 3D-to-2D projection.
  • an entity that maps 3D texture data on to projection planes can choose the six sides of an oriented or an axis aligned bounding box of a 3D point cloud as the initial set of projection planes.
  • the mapping of 3D surface parts on to the projection planes only maps the closest coherent surface onto the projections planes. For example, if there are two surfaces of the 3D object where one surface occludes the other surface in the direction of the 2D planes normal, then only the occluding surface is mapped on to the projection plane.
  • the occluded surface requires the generation of another projection plane for mapping.
  • the pose of the projections planes for the occluded points in the point cloud can be chosen such that it maximizes the rate-distortion performance for encoding the texture, depth and other auxiliary planes.
  • the capturing is carried out with multiple cameras and multiple light sources.
  • the outcome of the color capture is a pre-lit diffuse looking capture without sharp specular reflections.
  • the real-life specular reflections of the materials are often presented as those of rough materials. Later, when playing back the content, the captured model seems artificial and the specular reflections of the material are not natural-looking in the current lighting conditions.
  • a method which is disclosed in Figure 8, comprises obtaining (800) a plurality of material maps associated with an object of a three-dimensional (3D) video stream; obtaining (802) a projection of the 3D object represented by a point cloud, wherein the point cloud is represented by at least one 2D patch associated with a depth map;
  • the encoding phase comprises both obtaining a plurality of material maps of an object, for example by scanning the physical object in a static pose and obtaining a point cloud-based 3D video representation of the same object.
  • the 2D patches of the point cloud projections are aligned to the scanned high resolution materials by mapping the points of the material maps and points of the 2D patches. Both the material maps and the mapping are transmitted further, for example to a storage or a rendering client.
  • MPEG-I PCC point cloud compression
  • MPEG-I PCC is standardization activity of Moving Picture Experts Group to develop standardized 3D point cloud compression (PCC).
  • the aim is to support efficient and interoperable storage and exchange of 3D point clouds with the specified requirements for lossless and/or lossy coding of geometry coordinates, lossless and/or lossy coding of point cloud attributes data and support for time varying point clouds.
  • the depth values may not present the surface very accurately.
  • the depth map is only used for surface fitting to a world scale and not for the final rendered depth values.
  • the depth map data is included in a bitstream as compressed.
  • the depth map may be sent in lower resolution and/or the depth map may be compressed and quantized heavily, because the neighboring values do not need to be exact.
  • the rendering phase may utilize depth values taken from the fine detailed high resolution material textures, such as from the displacement map. Accordingly, the neighboring depth values can be matched to the range of depth changes in the high resolution textures.
  • said color texture map comprises only chroma components of the texture.
  • the rate of change and the difference of a value of U and V components to neighboring pixels is typically smooth, and for example, the MPEG-I PCC may apply a smoothing process for alleviating potential discontinuities of neighboring pixels, for example at patch boundaries.
  • the similarity of neighboring U and V components may significantly improve the compression efficiency of the texture data.
  • UV coordinates are compressed with regular video coding tools, such as according to HEVC encoding/decoding, and therefore the video texture compression is expected to work well.
  • the method further comprises creating chroma components for each frame of the video stream; and determining the mapping of chroma components of a 2D patch to chroma components of the material map as a patch chroma offset.
  • UV coordinates for the material textures are created and by applying a patch UV coordinate offset, the high resolution material texture pixel values can be directly mapped with linear interpolation.
  • any available methods such as pattern recognition or machine learning, may be used to match the 3D object(s) represented by a point cloud to the scanned objects(s) in the high resolution material textures.
  • the basic idea is that by detecting the shape and texture of the object as captured in the PCC-based video, and matching the shape and texture to the static model of the object, a 1 : 1 mapping between the static model with high resolution materials and the dynamic model of the PCC-based video capturing can be achieved with low bitrates.
  • the geometry (depth) stream may be encoded as patches, and the UV-texture stream maps to these same patches.
  • the stream contains patches and inside patches the UV-coordinates are local, i.e. a patch has a UV offset to textures, and the pixels inside said patch have UV offset values to the initial patch UV offset. Accordingly, the UV values for very large textures may be presented in a range used in typical video codecs (8 to 10 bits).
  • said material maps may further comprise one or more of the following:
  • an albedo / base color texture map provides a non-lit color texture of the surface.
  • a roughness map describes the surface irregularities that cause light diffusion, wherein the rougher surfaces have larger and dimmer looking highlights.
  • a metalness map is used to define which areas of the material are metallic, whereupon a bidirectional reflectance distribution function (BRDF) of said areas are changed accordingly.
  • BRDF bidirectional reflectance distribution function
  • a cavity map may be used for defining small scale occluded light and an ambient occlusion map, in turn, may be used for defining large scale occluded light.
  • Figure 9 shows an example of mapping the same UV coordinates of a patch to a plurality of material maps obtained from scanning the physical object.
  • Figure 9 shows only one patch (Patch 1) mapped to tiles of a patch atlas. Each tile is provided with UV coordinates. The UV coordinates of each tile may be mapped to a plurality of high resolution material maps (texture map 1, texture map 2, texture map 3, ...) of the scanned object.
  • An apparatus comprises at least one processor and at least one memory, said at least one memory stored with computer program code thereon, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to perform: obtaining a plurality of material maps associated with an object of a three-dimensional (3D) video stream; obtaining a projection of the 3D object represented by a point cloud, wherein the projection is represented by at least one 2D patch associated with a depth map; determining a mapping between points of the material maps and points of the 2D patch, wherein the material maps comprise at least one displacement map, at last one normal map, and at least one color texture map;
  • 3D three-dimensional
  • a decoding method comprises, as shown in Figure 10, receiving (1000) a plurality of material maps associated with an object of a three- dimensional (3D) video stream, wherein a point cloud of the object is represented by at least one 2D patch associated with a depth map; storing (1002) the plurality of material maps, wherein the material maps comprise at least one displacement map, at least one normal map and at least one color texture map; receiving (1004) an indication of a mapping between points of the material maps and points of the 2D patch; reconstructing (1006) geometry of the 2D patch based on the depth map, the displacement map, the normal map and the mapping between points of the stored material maps and the 2D patch; and reconstructing (1008) texture of the 2D patch based on the color texture map and the mapping between the points of the stored material maps and the 2D patch.
  • the decoding process utilizes the material maps obtained from the scanned object and the mapping to the between points of the material maps and points of the 2D patch and reconstructs the geometry of the 2D patch using the information from the depth map, the displacement map, the normal map and the mapping between points of the stored material maps and the 2D patch and the texture of the 2D patch based on the color texture map and the mapping between the points of the stored material maps and the 2D patch.
  • said color texture map comprises only chroma samples of the texture. Accordingly, the geometry (depth) and UV streams are decoded to obtain the UV coordinates, which map to texture map.
  • the texture map represents the actual object from all angles.
  • correct material textures are sampled from the correct locations.
  • the received bitstream may comprise additional metadata for indicating, per patch, to which material texture map said patch refers to.
  • the correct material texture map may be fetched for the mapping process.
  • the actual object is, for example, a human head or face
  • different positions or reformation of the object such as orientation of head or facial expressions
  • the method further comprises linearly
  • the UV coordinate values from the 2D patches when applied with their corresponding patch UV offsets can be directly mapped to the UV coordinates of the material textures.
  • the method further comprises reconstructing a coarse surface from the depth map; and offsetting the coarse surface by the displacement map to obtain a surface geometry to render.
  • an additional depth recreation is performed based on the streamed coarse depth and the additional geometry information contained in the precise high resolution material textures, such as displacement maps.
  • the coarse surface is reconstructed from the streamed depth data, possibly with an averaging filter to alleviate compression artefacts.
  • the method further comprises re-lighting at least part of the surfaces of the reconstructed object. Consequently, provided with correct physically based materials, the scene can be re-lighted with, for example, synthetic light sources or environment probes.
  • the traditional real-time PBR approach may be used to presenting the real-world captured content.
  • each patch is mapped to tiles in a patch atlas and encoded into separate color and geometry video streams that have a 1 : 1
  • each patch can be mapped to its corresponding region in the patch atlas and converted back into 3D geometry for rendering.
  • each patch may have additional attributes to define the mapping from the streamed UV coordinates to the material maps.
  • the additional attributes for defining the mapping from the streamed UV coordinates to the material maps may comprise one or more of the following:
  • Each material map may additionally have a scale factor, enabling different attributes to be encoded at different resolutions
  • Figure 11 shows an example of implementing the per-patch decoding process, wherein the metadata for defining the mapping from the streamed UV coordinates to the material maps is included.
  • the first line illustrates the reconstruction of the geometry stream, wherein the patch geometry stream is decoded, and from the highly compressed and/or quantized depth map values only a coarse geometry data for the depth is reconstructed.
  • a smoothing filtering may be applied for the coarse geometry data, and depth values taken from the high resolution material textures, such as from the
  • displacement map may be used to obtain the exact depth displacement.
  • the second line illustrates the reconstruction of the chroma component (UV) stream, wherein the UV stream is decoded and the UV coordinates of the patch are aligned to the UV coordinates of one or more material maps.
  • the third line illustrates the utilization of the metadata, wherein the additional attributes for defining the mapping from the streamed UV coordinates to the material maps are decoded and used in aligning the UV coordinates of the patch to the UV coordinates of one or more material maps.
  • the method further comprises transmitting the material maps once in the beginning of the video stream. Contrary to model deformation and illumination, the actual materials do not typically change, or change only intermittently and/or slowly. Therefore, the material maps may be transmitted once in the beginning of the video stream and cached for the duration of the playback. This is illustrated in the last line of Figure 11, where the cached material maps are included upon sampling the material maps.
  • the available material maps can be signalled, for example, as data block with a material attribute enumeration or bitmask signalling which material attribute map(s) the data block contains. Possible material attributes include, but are not limited to:
  • additional metadata may be used to signal the scale of the displacement, for example.
  • the attributes may also include an indication of the illumination incident on the model. While the illumination may be changing and thus increase the bandwidth required for the material attributes, this still enables the benefits of view-dependent PBR rendering.
  • Material maps may be also transmitted periodically or intermittently during the video stream to adapt to changes of objects and/or materials during the video stream.
  • a signal may be included in the stream in the form of, for example, SEI messages or other form of intermittent metadata.
  • Figure 12 illustrates the updating the material maps according to such signals. Decoding material map changes in the middle of the stream. Depending on the
  • the material update stream may be embedded as data blocks in the stream metadata, or it may be a dedicated auxiliary video stream.
  • the material update may be then stored in cache.
  • Example embodiments include:
  • “Material update” signal comprising an indication, e.g. a bitmask, of which materials are being updated, and the content of the indicated material maps, optionally compressed using an image compression algorithm.
  • the material maps may be included in their own video streams. Given that the material maps update infrequently, the average bitrate of such a video signal would be relatively low while still allowing for gradual change of surface properties.
  • the above embodiments may be used with pre-baked streaming approach as well.
  • the process can be changed so that the actual re-lighting happens on the server or a mobile network edge node and bakes all the offline rendered lighting information into the stream.
  • the geometry (depth) and color data is then streamed to the client for final rendering.
  • the above embodiments may provide various advantages. They enable rendering physically based material representation and real-time re-lighting for captured volumetric video with lowered bandwidth for streaming, while still enabling to render high quality and high resolution surfaces.
  • the embodiments enable to speed up the real-world video content creation with one time scanned precise materials.
  • the embodiments may also be extended easily with new materials and different materials for different material processing pipelines.
  • An apparatus comprises at least one processor and at least one memory, said at least one memory stored with computer program code thereon, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus at least to perform: receiving a plurality of material maps associated with an object of a three-dimensional (3D) video stream, wherein a point cloud of the object is represented by at least one 2D patch associated with a depth map; storing the plurality of material maps, wherein the material maps comprise at least one
  • displacement map at least one normal map and at least one color texture map
  • receiving an indication of a mapping between points of the material maps and points of the 2D patch reconstructing geometry of the 2D patch based on the depth map, the displacement map, the normal map and the mapping between points of the stored material maps and the 2D patch; and reconstructing texture of the 2D patch based on the color texture map and the mapping between the points of the stored material maps and the 2D patch.
  • said encoding may comprise one or more of the following: encoding source image data into a bitstream, encapsulating the encoded bitstream in a container file and/or in packet(s) or stream(s) of a communication protocol, and announcing or describing the bitstream in a content description, such as the Media Presentation Description (MPD) of ISO/IEC 23009-1 (known as MPEG-DASH) or the IETF Session Description Protocol (SDP).
  • MPD Media Presentation Description
  • SDP IETF Session Description Protocol
  • decoding may comprise one or more of the following: decoding image data from a bitstream,
  • bitstream decapsulating the bitstream from a container file and/or from packet(s) or stream(s) of a communication protocol, and parsing a content description of the bitstream
  • Embodiments of the inventions may be practiced in various components such as integrated circuit modules.
  • the design of integrated circuits is by and large a highly automated process.
  • Complex and powerful software tools are available for converting a logic level design into a semiconductor circuit design ready to be etched and formed on a semiconductor substrate.
  • Programs such as those provided by Synopsys, Inc. of Mountain View, California and Cadence Design, of San Jose, California automatically route conductors and locate components on a semiconductor chip using well established rules of design as well as libraries of pre stored design modules.
  • the resultant design in a standardized electronic format (e.g., Opus, GDSII, or the like) may be transmitted to a semiconductor fabrication facility or "fab" for fabrication.

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Abstract

La présente invention concerne divers procédés, appareils et produits-programmes d'ordinateur pour un codage vidéo.Un procédé comprend : la réception d'une pluralité de cartes matérielles associées à un objet d'un flux vidéo tridimensionnel (3D), un nuage de points de l'objet étant représenté par au moins un pavé 2D associé à une carte de profondeur; le stockage de la pluralité de cartes matérielles, les cartes matérielles comprenant au moins une carte de déplacement, au moins une carte normale et au moins une carte de texture colorée; la réception d'une indication d'un mappage entre des points des cartes matérielles et des points du pavé 2D; la reconstruction d'une géométrie du pavé 2D sur la base de la carte de profondeur, de la carte de déplacement, de la carte normale et du mappage entre des points des cartes matérielles stockées et du pavé 2D; et la reconstruction de la texture du pavé 2D sur la base de la carte de texture colorée et du mappage entre les points des cartes matérielles stockées et du pavé 2D.
PCT/FI2019/050389 2018-05-31 2019-05-20 Appareil, procédé et programme d'ordinateur pour vidéo volumétrique WO2019229293A1 (fr)

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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US11430155B2 (en) 2018-10-05 2022-08-30 Apple Inc. Quantized depths for projection point cloud compression
WO2021240069A1 (fr) * 2020-05-27 2021-12-02 Nokia Technologies Oy Couches de texture de décalage pour codage et signalisation de réflexion et réfraction pour vidéo immersive et procédés pour vidéo volumétrique multicouche associés
CN112598778A (zh) * 2020-08-28 2021-04-02 国网陕西省电力公司西咸新区供电公司 一种基于改进的纹理贴图算法的vr三维重建技术
CN112598778B (zh) * 2020-08-28 2023-11-14 国网陕西省电力公司西咸新区供电公司 一种基于改进的纹理贴图算法的vr三维重建方法
CN112422848A (zh) * 2020-11-17 2021-02-26 深圳市歌华智能科技有限公司 一种基于深度图和彩色图的视频拼接方法
CN112422848B (zh) * 2020-11-17 2024-03-29 深圳市歌华智能科技有限公司 一种基于深度图和彩色图的视频拼接方法
CN113178014A (zh) * 2021-05-27 2021-07-27 网易（杭州）网络有限公司 场景模型渲染方法、装置、电子设备和存储介质
WO2023148730A1 (fr) * 2022-02-06 2023-08-10 Yoom.Com Ltd Segmentation de matériaux
CN118138741A (zh) * 2024-05-08 2024-06-04 四川物通科技有限公司 基于元宇宙的裸眼3d数据通信方法

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