Patent Publication Number: US-2022222890-A1

Title: Method and apparatus for media scene description

Description:
CROSS-REFERENCE TO RELATED APPLICATION 
     This application claims priority from U.S. Provisional Application No. 63/137,274, filed on Jan. 14, 2021, the disclosures of which is incorporated herein by reference in its entirety. 
    
    
     FIELD 
     Embodiments of the present disclosure relate to system design to support media objects using a 3D modeling syntax, implement media syntax to support various media codecs, containers, and formats, manage media storage and delivery method through predefined programming interfaces, and provide media buffer control and rendering functions. 
     BACKGROUND 
     The Graphics Language Transmission Format (glTF) is an API-neutral runtime asset 3D modeling delivery format. Compared with traditional 3D modeling tools, glTF provides a more efficient, extensible, interoperable format for the transmission and loading of 3D content. glTF2.0 is the most recent version of the glTF specification written by the Khronos 3D Group. This format supports a simple scene graph format that is generally capable of supporting static (untimed) objects in scenes, including “png” and “jpeg” image formats. glTF2.0 supports simple animations, including support for translate, rotate, and scale, of basic shapes described using the glTF primitives, i.e. for geometric objects. glTF2.0 does not support timed media, and hence does not support video nor audio. 
     “Information technology—Coding of audiovisual objects—Part 12: ISO base media file format”, ISO/IEC 14496-12 (December 2015), “Draft of FDIS of ISO/IEC 23000-19 Common Media Application Format for Segmented Media”, ISO/IEC JTC1/SC29/WG11 MPEG117/16819 (April 2017); and “Text of ISO/IEC FDIS 23009-1 4th edition”, ISO/IEC JTC 1/SC 29/WG 11 N18609 (August 2019), and the glTF2.0 specification are incorporated herein by reference in their entirety. 
     SUMMARY 
     According to an embodiment, a method of managing media storage and delivery is implemented by at least one processor and includes obtaining, by a media access function (MAF), a Graphics Language Transmission Format (glTF) file corresponding to a scene; obtaining from the glTF file a uniform resource locator (URL) parameter indicating a binary data blob; determining that the binary data blob has a Concise Binary Object Representation (CBOR) format; converting the binary data blob into an object having a JavaScript Object Notation (JSON) format using a CBOR parser function implemented by the MAF; and obtaining media content corresponding to the scene based on the object. 
     According to an embodiment, a device for managing media storage and delivery includes at least one memory configured to store program code; and at least one processor configured to read the program code and operate as instructed by the program code, the program code including: first obtaining code configured to cause the at least one processor to obtain, by a media access function (MAF), a Graphics Language Transmission Format (glTF) file corresponding to a scene; second obtaining code configured to cause the at least one processor to obtain from the glTF file a uniform resource locator (URL) parameter indicating a binary data blob; determining code configured to cause the at least one processor to determine that the binary data blob has a Concise Binary Object Representation (CBOR) format; converting code configured to cause the at least one processor to convert the binary data blob into an object having a JavaScript Object Notation (JSON) format using a CBOR parser function implemented by the MAF; and third obtaining code configured to cause the at least one processor to obtain media content corresponding to the scene based on the object. 
     According to an embodiment, a non-transitory computer-readable medium stores instructions, including one or more instructions that, when executed by at least one processor of a device for managing media storage and delivery, are configured to cause the at least one processor to: obtain, by a media access function (MAF), a Graphics Language Transmission Format (glTF) file corresponding to a scene; obtain from the glTF file a uniform resource locator (URL) parameter indicating a binary data blob; determine that the binary data blob has a Concise Binary Object Representation (CBOR) format; convert the binary data blob into an object having a JavaScript Object Notation (JSON) format using a CBOR parser function implemented by the MAF; and obtain media content corresponding to the scene based on the object. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Further features, the nature, and various advantages of the disclosed subject matter will be more apparent from the following detailed description and the accompanying drawings in which: 
         FIG. 1  is a diagram of an environment in which methods, apparatuses and systems described herein may be implemented, according to embodiments. 
         FIG. 2  is a block diagram of example components of one or more devices of  FIG. 1 , according to embodiments. 
         FIG. 3  is a schematic illustration of glTF scene description objects, according to embodiments. 
         FIG. 4  is a schematic illustration of the media scene description system reference architecture, according to embodiments. 
         FIG. 5  is an example of glTF JavaScript Object Notation (JSON) format representation, according to embodiments. 
         FIG. 6  is an example of MPEG glTF extension, according to embodiments. 
         FIG. 7A  is an illustration of a file having a JSON format, according to embodiments. 
         FIG. 7B  is an illustration of a file having a CBOR format, according to embodiments. 
         FIG. 8  is an illustration of an example of glTF syntax, according to embodiments. 
         FIGS. 9A-9C  are diagrams of example processes for managing media storage and delivery according to embodiments. 
     
    
    
     DETAILED DESCRIPTION 
       FIG. 1  is a diagram of an environment  100  in which methods, apparatuses, and systems described herein may be implemented, according to embodiments. As shown in  FIG. 1 , the environment  100  may include a user device  110 , a platform  120 , and a network  130 . Devices of the environment  100  may interconnect via wired connections, wireless connections, or a combination of wired and wireless connections. 
     The user device  110  includes one or more devices capable of receiving, generating, storing, processing, and/or providing information associated with platform  120 . For example, the user device  110  may include a computing device (e.g., a desktop computer, a laptop computer, a tablet computer, a handheld computer, a smart speaker, a server, etc.), a mobile phone (e.g., a smart phone, a radiotelephone, etc.), a wearable device (e.g., a pair of smart glasses or a smart watch), or a similar device. In some implementations, the user device  110  may receive information from and/or transmit information to the platform  120 . 
     The platform  120  includes one or more devices as described elsewhere herein. In some implementations, the platform  120  may include a cloud server or a group of cloud servers. In some implementations, the platform  120  may be designed to be modular such that software components may be swapped in or out depending on a particular need. As such, the platform  120  may be easily and/or quickly reconfigured for different uses. 
     In some implementations, as shown, the platform  120  may be hosted in a cloud computing environment  122 . Notably, while implementations described herein describe the platform  120  as being hosted in the cloud computing environment  122 , in some implementations, the platform  120  may not be cloud-based (i.e., may be implemented outside of a cloud computing environment) or may be partially cloud-based. 
     The cloud computing environment  122  includes an environment that hosts the platform  120 . The cloud computing environment  122  may provide computation, software, data access, storage, etc. services that do not require end-user (e.g., the user device  110 ) knowledge of a physical location and configuration of system(s) and/or device(s) that hosts the platform  120 . As shown, the cloud computing environment  122  may include a group of computing resources  124  (referred to collectively as “computing resources  124 ” and individually as “computing resource  124 ”). 
     The computing resource  124  includes one or more personal computers, workstation computers, server devices, or other types of computation and/or communication devices. In some implementations, the computing resource  124  may host the platform  120 . The cloud resources may include compute instances executing in the computing resource  124 , storage devices provided in the computing resource  124 , data transfer devices provided by the computing resource  124 , etc. In some implementations, the computing resource  124  may communicate with other computing resources  124  via wired connections, wireless connections, or a combination of wired and wireless connections. 
     As further shown in  FIG. 1 , the computing resource  124  includes a group of cloud resources, such as one or more applications (“APPs”)  124 - 1 , one or more virtual machines (“VMs”)  124 - 2 , virtualized storage (“VSs”)  124 - 3 , one or more hypervisors (“HYPs”)  124 - 4 , or the like. 
     The application  124 - 1  includes one or more software applications that may be provided to or accessed by the user device  110  and/or the platform  120 . The application  124 - 1  may eliminate a need to install and execute the software applications on the user device  110 . For example, the application  124 - 1  may include software associated with the platform  120  and/or any other software capable of being provided via the cloud computing environment  122 . In some implementations, one application  124 - 1  may send/receive information to/from one or more other applications  124 - 1 , via the virtual machine  124 - 2 . For example, the application  124 - 1  may provide media streaming that includes, but is not limited to, audio streaming, visual streaming, object description stream, scene description stream, etc. A scene description generally refers to a descriptor that describes a scene. A scene can generally refer to any 2D, 3D, and/or immersive objects and their associated properties, commands, and/or behaviors. The scene description can be transmitted in the form of a scene graph, which is a hierarchical representation of audio, video and graphical objects. Note that scene description can be transmitted independently from other types of streams, e.g., audio stream, visual stream, object description stream, etc. 
     The virtual machine  124 - 2  includes a software implementation of a machine (e.g., a computer) that executes programs like a physical machine. The virtual machine  124 - 2  may be either a system virtual machine or a process virtual machine, depending upon use and degree of correspondence to any real machine by the virtual machine  124 - 2 . A system virtual machine may provide a complete system platform that supports execution of a complete operating system (“OS”). A process virtual machine may execute a single program, and may support a single process. In some implementations, the virtual machine  124 - 2  may execute on behalf of a user (e.g., the user device  110 ), and may manage infrastructure of the cloud computing environment  122 , such as data management, synchronization, or long-duration data transfers. 
     The virtualized storage  124 - 3  includes one or more storage systems and/or one or more devices that use virtualization techniques within the storage systems or devices of the computing resource  124 . In some implementations, within the context of a storage system, types of virtualizations may include block virtualization and file virtualization. Block virtualization may refer to abstraction (or separation) of logical storage from physical storage so that the storage system may be accessed without regard to physical storage or heterogeneous structure. The separation may permit administrators of the storage system flexibility in how the administrators manage storage for end users. File virtualization may eliminate dependencies between data accessed at a file level and a location where files are physically stored. This may enable optimization of storage use, server consolidation, and/or performance of non-disruptive file migrations. 
     The hypervisor  124 - 4  may provide hardware virtualization techniques that allow multiple operating systems (e.g., “guest operating systems”) to execute concurrently on a host computer, such as the computing resource  124 . The hypervisor  124 - 4  may present a virtual operating platform to the guest operating systems, and may manage the execution of the guest operating systems. Multiple instances of a variety of operating systems may share virtualized hardware resources. 
     The network  130  includes one or more wired and/or wireless networks. For example, the network  130  may include a cellular network (e.g., a fifth generation (5G) network, a long-term evolution (LTE) network, a third generation (3G) network, a code division multiple access (CDMA) network, etc.), a public land mobile network (PLMN), a local area network (LAN), a wide area network (WAN), a metropolitan area network (MAN), a telephone network (e.g., the Public Switched Telephone Network (PSTN)), a private network, an ad hoc network, an intranet, the Internet, a fiber optic-based network, or the like, and/or a combination of these or other types of networks. 
     The number and arrangement of devices and networks shown in  FIG. 1  are provided as an example. In practice, there may be additional devices and/or networks, fewer devices and/or networks, different devices and/or networks, or differently arranged devices and/or networks than those shown in  FIG. 1 . Furthermore, two or more devices shown in  FIG. 1  may be implemented within a single device, or a single device shown in  FIG. 1  may be implemented as multiple, distributed devices. Additionally, or alternatively, a set of devices (e.g., one or more devices) of the environment  100  may perform one or more functions described as being performed by another set of devices of the environment  100 . 
       FIG. 2  is a block diagram of example components of one or more devices of  FIG. 1 . The device  200  may correspond to the user device  110  and/or the platform  120 . As shown in  FIG. 2 , device  200  may include a bus  210 , a processor  220 , a memory  230 , a storage component  240 , an input component  250 , an output component  260 , and a communication interface  270 . 
     The bus  210  includes a component that permits communication among the components of the device  200 . The processor  220  is implemented in hardware, firmware, or a combination of hardware and software. The processor  220  is a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a microprocessor, a microcontroller, a digital signal processor (DSP), a field-programmable gate array (FPGA), an application-specific integrated circuit (ASIC), or another type of processing component. In some implementations, the processor  220  includes one or more processors capable of being programmed to perform a function. The memory  230  includes a random access memory (RAM), a read only memory (ROM), and/or another type of dynamic or static storage device (e.g., a flash memory, a magnetic memory, and/or an optical memory) that stores information and/or instructions for use by the processor  220 . 
     The storage component  240  stores information and/or software related to the operation and use of the device  200 . For example, the storage component  240  may include a hard disk (e.g., a magnetic disk, an optical disk, a magneto-optic disk, and/or a solid state disk), a compact disc (CD), a digital versatile disc (DVD), a floppy disk, a cartridge, a magnetic tape, and/or another type of non-transitory computer-readable medium, along with a corresponding drive. 
     The input component  250  includes a component that permits the device  200  to receive information, such as via user input (e.g., a touch screen display, a keyboard, a keypad, a mouse, a button, a switch, and/or a microphone). Additionally, or alternatively, the input component  250  may include a sensor for sensing information (e.g., a global positioning system (GPS) component, an accelerometer, a gyroscope, and/or an actuator). The output component  260  includes a component that provides output information from the device  200  (e.g., a display, a speaker, and/or one or more light-emitting diodes (LEDs)). 
     The communication interface  270  includes a transceiver-like component (e.g., a transceiver and/or a separate receiver and transmitter) that enables the device  200  to communicate with other devices, such as via a wired connection, a wireless connection, or a combination of wired and wireless connections. The communication interface  270  may permit the device  200  to receive information from another device and/or provide information to another device. For example, the communication interface  270  may include an Ethernet interface, an optical interface, a coaxial interface, an infrared interface, a radio frequency (RF) interface, a universal serial bus (USB) interface, a Wi-Fi interface, a cellular network interface, or the like. 
     The device  200  may perform one or more processes described herein. The device  200  may perform these processes in response to the processor  220  executing software instructions stored by a non-transitory computer-readable medium, such as the memory  230  and/or the storage component  240 . A computer-readable medium is defined herein as a non-transitory memory device. A memory device includes memory space within a single physical storage device or memory space spread across multiple physical storage devices. 
     Software instructions may be read into the memory  230  and/or the storage component  240  from another computer-readable medium or from another device via the communication interface  270 . When executed, software instructions stored in the memory  230  and/or the storage component  240  may cause the processor  220  to perform one or more processes described herein. Additionally, or alternatively, hardwired circuitry may be used in place of or in combination with software instructions to perform one or more processes described herein. Thus, implementations described herein are not limited to any specific combination of hardware circuitry and software. 
     The number and arrangement of components shown in  FIG. 2  are provided as an example. In practice, the device  200  may include additional components, fewer components, different components, or differently arranged components than those shown in  FIG. 2 . Additionally, or alternatively, a set of components (e.g. one or more components) of the device  200  may perform one or more functions described as being performed by another set of components of the device  200 . 
     Referring to  FIG. 3 , the Graphics Language Transmission Format (glTF) is an application programming interface (API)-neutral runtime asset 3D modeling delivery format. Compared with traditional 3D modeling tools, glTF provides a more efficient, extensible, interoperable format for the transmission and loading of 3D content. 
     A glTF scene may be a combination of multiple glTF assets. The glTF assets may be JavaScript Object Notation (JSON)-formatted files containing a full scene description which may include, for example, a scene object  301 , node  302 , camera  303 , mesh  304 , light  305 , animation  306 , accessor  307 , material  308 , skin  309 , bufferview  310 , technique  311 , texture  312 , buffer  313 , program  314 , image  315 , sampler  316 , shader  317 , plus supporting external data. 
     glTF also supports external data sources which may be referenced in any above-mentioned scene objects. In embodiments, a binary file may be used for animation  306  or other buffer-based data  313 . An image file may be used for object textures  312 . 
     Referring to  FIG. 5 , as mentioned above, a glTF scene may be organized in JSON format. A glTF asset may include zero or more scenes  503 , which may be the set of visual objects to render. Scenes may be defined in a scene array. In example illustrated in  FIG. 5 , there is a single scene  506  with a single node  501 , although embodiments are not limited thereto. Various parameters that may be associated with each node object. For example, name  502  may specify the name of the node object, and scene name  504  may specify the name of the single scene. 
     The glTF scene assets may be consumed by a presentation engine for rendering a 3D or immersive scene to users. The existing glTF syntax only supports 3D objects including static or computer-generated animations. There is no support for media types such as video or audio, let alone rendering those video/audio media types. 
     Meanwhile, existing glTF cannot describe a scene using geographical coordinate systems, which in some media presentation scenarios, such a feature is desired. 
     Therefore, there is a need to extend the glTF to support media types includes traditional 2D flat video, immersive media content such as virtual reality (VR), augmented reality (AR), extended reality (XR), and spatial audios. This may require an extension to support video/audio syntax and a system for media deliveries and render 
     Moving Picture Experts Group (MPEG) defines some extensions on top of the glTF specification to support immersive media content. Referring to  FIG. 3 , new extensions are MPEG_media  330 , MPEG_scene_dynamic  331 , MPEG_texture_video  333 , MEPG_animation_timing  332 , MPEG_audio_spatial  334 , MPEG_accessor_timed  335 , MPEG_buffer_circular  336 . In  FIG. 3  generally, elements with rounded outlines, for example elements  301 - 317 , may be glTF elements, and elements with square outlines, for example elements  330 - 336 , may correspond to MPEG-based extensions of the glTF specification, although embodiments are not limited thereto. 
     If MPEG_media  330  as a root identifier, if specified, then MPEG_media may be supported. Referring to  FIG. 6 , the syntax to support MPEG media may be declared as the top-level JSON syntax. Syntax from  601  to  604  in  FIG. 6  may be presented exactly as shown if supported. 
     Scene Updates may be expressed using the JSON Patch protocol and MPEG_scene_dynamic  331  may be used to support JSON patch protocol. 
     MPEG texture video extension, identified by MPEG_texture_video  333 , may provide the possibility to link a glTF texture object to MPEG media and its respective track, listed by an MPEG_media object. MPEG texture video extension may also provide a reference to the MPEG_accessor_timed  335 , where the decoded timed texture will be made available. 
     The MPEG_audio_spatial  334  extension may support multiple audio types. 
     In order to support timed data access, the buffer element may be extended to provide circular buffer functionality. The extension is named MPEG_buffer_circular 336 and may be included as part of the glTF “buffers” objects, for example buffer  313 . 
     Above MEPG extensions may allow for the creation of immersive experiences using glTF. Eventually the glTF assets with MPEG extension may be used to be load into a rendering engine for visualization. 
     Referring to  FIG. 4 , a reference media scene description architecture  400  illustrates an example of how MPEG extensions may be used to support media type such as audio/video. The media contents may be retrieved using a Media Retrieval Engine and Media Access Functions (MAF)  402  from external sources such as a media cloud  401 , processed using video decoder  403 , audio decoder  404 , and other data compressor  405 , buffered in video buffer  406 , audio buffer  407 , and other buffer  408 , and rendered by a presentation engine  409 . In some cases, media content may be stored in local storage  410 . MAFs provide a framework for integration of elements from several MPEG standards into a single specification that is suitable for specific but widely usable applications. For example, MAFs can specify how to combine metadata with timed media information for a presentation in a well-defined format that facilitates interchange, management, editing, and presentation of the media. The presentation may be ‘local’ to the system or may be accessible via a network or other stream delivery mechanism. 
     Referring to  FIG. 4 , the MPEG scene description extensions may decouple the Presentation Engine  409  from the Media Retrieval Engine  402 . Presentation Engine  409  and Media Retrieval Engine  402  may communicate through the predefined programming interfaces, which allows the Presentation Engine  409  to request media data required for the rendering of the scene. The Media Retrieval Engine  402  may retrieve the requested media and make it available in a timely manner and in a format that can be immediately processed by the Presentation Engine  409 . For instance, a requested media asset may be compressed and residing in the network, so the Media Retrieval Engine  402  will retrieve and decode the asset and pass the resulting media data to the Presentation Engine  409  for rendering. The media data may be passed in form of buffers from the Media Retrieval Engine  402  to the Presentation Engine  409 . The requests for media data may be passed through a Media Retrieval API from the Presentation Engine  409  to the Media Retrieval Engine  402 . For flexible use of video decoding resource, the Video Decoder  403  may be used. When the Video Decoder  403  is used, the Presentation Engine  409  may provide information for input formatting and output formatting to the Video Decoder  403  through Application Configuration APIs. 
     As discussed above, glTF syntax may be expressed in a JSON file. The Internet Engineering Task Force (IETF) Concise Binary Object Representation (CBOR) may represent a concise data format compared with the traditional JSON format. CBOR relates to similar data objects like JSON in a name/value pair format, but expressed in a binary and compact way, also with much more support with key-value types. A size of a file in CBOR format may be smaller than a corresponding file in JSON format. In some cases, the CBOR file may be more than 50% smaller than the corresponding JSON file. CBOR is registered in Internet Assigned Numbers Authority (IANA) as “application/cbor”. 
     CBOR may be used as one of the glTF interchangeable compressed file formats which also has been widely supported due to its compact data size and interchangeability with JSON. 
     Information in CBOR is stored in binary form. Because many use cases for information includes machines to understand the data, a binary data format may have speed advantages over human-readable data formats like JSON or XML which may need to be parsed each time the computer or machine is used to understand the data stored. 
       FIG. 7A  illustrates an example of a file in JSON format, and  FIG. 7B  illustrates an example of a corresponding file in CBOR format. For example, the character “a” ( 711 ) in the JSON formatted file of  FIG. 7A  may correspond to 0x61 ( 721 ) in the CBOR formatted file of  FIG. 7B . Similarly, the character “b” ( 712 ) in the JSON formatted file of  FIG. 7A  may correspond to 0x62 ( 722 ) in the CBOR formatted file of  FIG. 7B , and the character “c” ( 713 ) in the JSON formatted file of  FIG. 7A  may correspond to 0x63 ( 723 ) in the CBOR formatted file of  FIG. 7B . 
     The usage of CBOR compared with JSON for scene description may bring advantages in terms of small data size, support of multiple key-value types instead of just String object in JSON. Function programming interfaces may be used in the presented media scene description reference architecture, more precisely in the media access function module. 
     Because the support of CBOR by glTF is gaining popularity, such support may be added into MPEG scene description in order to, for example, increase glTF file format interoperability, reduce file size for local storage or cache, and reduce glTF file transfer latency with minimum processing power at MAF  402 . 
     A CBOR parser function according to embodiments may be implemented by MAF  402  to translate CBOR input into glTF native supported JSON format and also could be used as a file compressor to save the large glTF file into local storage or cache  410 . 
     The CBOR parser API offers one of the methods such as cbor2Json( ), json2Cbor and save( ), as shown in the Table I below: 
     
       
         
           
               
               
             
               
                 TABLE 1 
               
               
                   
               
               
                 Method 
                 Brief Description 
               
               
                   
               
             
            
               
                 cbor2Json (FILE) 
                 Convert a CBOR format into a JSON format 
               
               
                 json2Cbor (FILE) 
                 Convert a JSON format into a CBOR format 
               
               
                 cbor2Json (Object) 
                 Convert a CBOR data blob into a JSON format 
               
               
                   
               
            
           
         
       
     
     A detailed interface description may be as follows: 
     
       
         
           
               
               
             
               
                   
                   
               
             
            
               
                   
                 interface InputFileParser { 
               
               
                   
                   readonly attribute FILE inputFileName; 
               
               
                   
                  readonly attribute FILE outputFilename; 
               
               
                   
                  readonly attribute CBOR cborDataBlob; 
               
               
                   
                   FILE cbor2Json( )(FILE cborInput); 
               
               
                   
                  FILE json2Cbor(FILE jsonInput); 
               
               
                   
                  FILE  cbor2Json(CBOR cborDataBlob); 
               
               
                   
                   bool save( ); 
               
               
                   
                 }; 
               
               
                   
                   
               
            
           
         
       
     
     The above proposed functions may be used for example in various scenarios as follows. 
     Referring to  FIG. 8 , a glTF “url” or “uri” syntax may point to a CBOR binary data blob ( 802 ). In embodiments, there may be two ways to specify if binary is indeed a CBOR data format. According to Example 1, a Multipurpose Internet Mail Extension (MIME) type may be signaled which specifies a “mimeTypes” with “applicationicbor” ( 801 ). According to Example 2, a prefix “application/cbor;” may be included in front of actual binary data. Examples 1 and 2 may be used together. In any case, a function called “cbor2Json(Object)” which takes a CBOR binary data may be called to parse the CBOR file format into a JSON. 
     If an input glTF is in CBOR format, the output may be a glTF by using cbor2Json( ) API 
     If an input is in a native glTF format, then no conversion may be necessary. 
     For local storage or cache purpose, a glTF file may be saved as a CBOR by using json2Cbor( ) and save( ) interface. 
     Accordingly, embodiments may relate to methods of providing glTF file format interoperability with CBOR, reducing file size for local storage or cache, increasing, data transfer speed, reducing file transfer latency. 
     Referring to  FIGS. 9A-9C , processes  900 A,  900 B, and  900 C for managing media storage and delivery are described below. 
       FIG. 9A  is a flowchart of an example process  900 A for managing media storage and delivery. 
     As shown in  FIG. 9A , process  900 A may include obtaining, by a media access function (MAF), a glTF file corresponding to a scene (block  911 ). In embodiments, the MAF may correspond to MAF  402 . 
     As further shown in  FIG. 9A , process  900 A may include obtaining from the glTF file a uniform resource locator (URL) parameter indicating a binary data blob (block  912 ). 
     As further shown in  FIG. 9A , process  900 A may include determining that the binary data blob has the CBOR format (block  913 ). 
     As further shown in  FIG. 9A , process  900 A may include converting the binary data blob into an object having the JSON format using a CBOR parser function implemented by the MAF (block  914 ). 
     As shown in  FIG. 9A , process  900 A may include obtaining media content corresponding to the scene based on the object (block  914 ). 
     In embodiments, the object having the JSON format may be larger than the binary data blob having the CBOR format. 
     In embodiments, the binary data blob may be determined to have the CBOR format based on a Multipurpose Internet Mail Extension (MIME) type that is signaled in the glTF file. 
     In embodiments, the binary data blob may be determined to have the CBOR format based on a prefix included at a beginning of the binary data blob. 
     In embodiments, the binary data blob may be determined to have the CBOR format based on a Multipurpose Internet Mail Extension (MIME) type that is signaled in the glTF file and a prefix included at a beginning of the binary data blob. 
     In embodiments, the MAF may be included in a Moving Picture Experts Group (MPEG) scene description architecture. 
     In embodiments, the CBOR parser function may be implemented using an application programming interface associated with the MAF. 
       FIG. 9B  is a flowchart of an example process  900 B for managing media storage and delivery. In embodiments, one or more blocks of process  900 B may be performed in combination with one or more blocks of process  900 A. For example, one or more blocks of process  900 B may be performed after one or more blocks of process  900 A. 
     As further shown in  FIG. 9B , process  900 B may include determining that the glTF file has a CBOR format (block  921 ). 
     As shown in  FIG. 9B , process  900 B may include converting the glTF file into a converted glTF file having a JSON format using a CBOR parser function implemented by the MAF (block  922 ). In embodiments, this CBOR parser function may be different from the CBOR parser function used in block  914 . 
     In embodiments, the converted glTF file having the JSON format may be larger than the glTF file having the CBOR format. 
       FIG. 9C  is a flowchart of an example process  900 C for managing media storage and delivery. In embodiments, one or more blocks of process  900 C may be performed in combination with one or more blocks of processes  900 A and/or  900 B. For example, one or more blocks of process  900 C may be performed after one or more blocks of process  900 A, or after one or more blocks of process  900 B. 
     As shown in  FIG. 9C , process  900 C may include re-converting the converted glTF file into a re-converted glTF having the CBOR format using a JSON parser function implemented by the MAF (block  931 ). 
     As further shown in  FIG. 9C , process  900 C may include storing the re-converted glTF file in at least one of a local storage or a cache (block  932 ). 
     Although  FIGS. 9A-9C  show example blocks of processes  900 A,  900 B, and  900 C, in some implementations, of processes  900 A,  900 B, and  900 C may include additional blocks, fewer blocks, different blocks, or differently arranged blocks than those depicted in  FIGS. 9A-9C . Additionally, or alternatively, two or more of the blocks of processes of processes  900 A,  900 B, and  900 C may be performed in parallel. In embodiments, any one or more blocks of processes  900 A,  900 B, and  900 C may be combined with any other one or more blocks of processes  900 A,  900 B, and  900 C in any order, and any one or more of any blocks of processes  900 A,  900 B, and  900 C may be split or combined as desired. 
     Further, the proposed methods may be implemented by processing circuitry (e.g., one or more processors or one or more integrated circuits). In one example, the one or more processors execute a program that is stored in a non-transitory computer-readable medium to perform one or more of the proposed methods. 
     The foregoing disclosure provides illustration and description, but is not intended to be exhaustive or to limit the implementations to the precise form disclosed. Modifications and variations are possible in light of the above disclosure or may be acquired from practice of the implementations. 
     It will be apparent that systems and/or methods, described herein, may be implemented in different forms of hardware, firmware, or a combination of hardware and software. The actual specialized control hardware or software code used to implement these systems and/or methods is not limiting of the implementations. Thus, it should be understood that software and hardware may be designed to implement the systems and/or methods based on the description herein. 
     Even though particular combinations of features are recited in the claims and/or disclosed in the specification, these combinations are not intended to limit the disclosure of possible implementations. In fact, many of these features may be combined in ways not specifically recited in the claims and/or disclosed in the specification. Although each dependent claim listed below may directly depend on only one claim, the disclosure of possible implementations includes each dependent claim in combination with every other claim in the claim set. 
     No element, act, or instruction used herein should be construed as critical or essential unless explicitly described as such. Also, as used herein, the articles “a” and “an” are intended to include one or more items, and may be used interchangeably with “one or more.” Furthermore, as used herein, the term “set” is intended to include one or more items (e.g., related items, unrelated items, a combination of related and unrelated items, etc.), and may be used interchangeably with “one or more.” Where only one item is intended, the term “one” or similar language is used. Also, as used herein, the terms “has,” “have,” “having,” or the like are intended to be open-ended terms. Further, the phrase “based on” is intended to mean “based, at least in part, on” unless explicitly stated otherwise.