Abstract:
A device may encapsulate video data such that Supplemental Enhancement Information (SEI) messages are stored separately from a sequence of coded video pictures described by the SEI messages. An example device includes a control unit configured to generate one or more SEI messages separate from the coded video pictures, wherein the SEI messages describe respective ones of the sequence of coded video pictures and include elements common to more than one of the coded video pictures, and an output interface configured to output the SEI messages separately from the sequence of coded video pictures. An example destination device may receive the SEI messages separately from the coded video pictures and render the coded video pictures using the SEI messages.
Abstract:
This disclosure describes techniques relevant to HTTP streaming of media data. According to these techniques, a server device may signal a byte range for at least one intra-decodable (I-frame) of a video fragment. According to the techniques of this disclosure, a client device may communicate a request to a server device to retrieve the at least one I-frame based on the signaled byte range, and use the retrieved I-frame to provide a high speed version of a video presentation that includes the at least one I-frame. A high speed version of a video presentation may be a trick mode of the video presentation, such as a fast forward or fast rewind version of the video presentation.
Abstract:
An asymmetric frame of a coded video bitstream may include a first resolution picture of a left view and a reduced resolution picture of a right view, where the left and right views form a stereo view pair for three-dimensional video playback. In addition, the reduced resolution frame may be predicted relative to a picture of the left view. In one example, an apparatus includes a video encoder configured to encode a first picture of a first view of a scene to produce an encoded picture with a first resolution, encode at least a portion of a second picture of a second view of the scene relative to a reference picture of the first view to produce an encoded picture with a reduced resolution relative to the first resolution, and output the encoded first resolution picture and the encoded reduced resolution picture in a common bitstream.
Abstract:
A method and system for garbage collection in a virtualization environment. The virtualization environment includes a virtual machine hypervisor, at least one guest operating system, and at least one application program that runs on each guest operating system. The application program performs memory management using a garbage collection mechanism. The method includes, in response to an operating environment of the application program initiating garbage collection, the garbage collector requesting the guest operating system to assign a memory space and in response, the guest operating system assigns the memory space to the garbage collector. Then garbage collector marks live objects in an original memory space of the application program, and replicates the marked live objects to the assigned memory space. Finally, the garbage collector releases the original memory space of the application program to the guest operating system.
Abstract:
A block-request streaming system provides for improvements in the user experience and bandwidth efficiency of such systems, typically using an ingestion system that generates data in a form to be served by a conventional file server (HTTP, FTP, or the like), wherein the ingestion system intakes content and prepares it as files or data elements to be served by the file server. The system might include controlling the sequence, timing and construction of block requests, time based indexing, variable block sizing, optimal block partitioning, control of random access point placement, including across multiple presentation versions, dynamically updating presentation data, and/or efficiently presenting live content and time shifting.
Abstract:
Joint coding of depth map video and texture video is provided, where a motion vector for a texture video is predicted from a respective motion vector of a depth map video or vice versa. For scalable video coding, depth map video is coded as a base layer and texture video is coded as an enhancement layer(s). Inter-layer motion prediction predicts motion in texture video from motion in depth map video. With more than one view in a bit stream (for multi view coding), depth map videos are considered monochromatic camera views and are predicted from each other. If joint multi-view video model coding tools are allowed, inter-view motion skip issued to predict motion vectors of texture images from depth map images. Furthermore, scalable multi-view coding is utilized, where interview prediction is applied between views in the same dependency layer, and inter-layer (motion) prediction is applied between layers in the same view.
Abstract:
A video coder may utilize large macroblocks having more than 16×16 pixels. Syntax for the large macroblocks may define whether a bitstream includes large macroblocks, such as superblocks having 64×64 pixels or bigblocks having 32×32 pixels. The syntax may be included in a slice header or a sequence parameter set. The large macroblocks may also be encoded according to a large macroblock syntax. The bitstream may further include syntax data that indicates a level value based on whether the bitstream includes any of the large macroblocks, for example, as a smallest-sized luminance prediction block. A decoder may use the level value to determine whether the decoder is capable of decoding the bitstream.
Abstract:
A method for analyzing sentiment comprising: collecting an object from an external content repository, the collected objects forming a content database; extracting a snippet related to the subject from the content database; calculating a sentiment score for the snippet; classifying the snippet into a sentiment category; creating sentiment taxonomy using the sentiment categories, the sentiment taxonomy classifying the snippets as positive, negative or neutral; identifying topic words within the sentiment taxonomy; classifying the topic words as a sentiment topic word candidates or a non-sentiment topic word candidate, filtering the non-sentiment topic word candidates; identifying the frequency of the non-sentiment topic words in each of the sentiment categories; identifying the importance of the non-sentiment topic word for each of the sentiment categories; and, ranking the topic word, wherein the rank is calculated by combining the frequency of the topic words in each of the categories with its importance.
Abstract:
A method for dynamically adjusting resources among a plurality of co-existing applications comprises the steps of: building a relation model between a request number and resource consumption of said plurality of applications; obtaining at multiple sampling moments a request number and resource consumption of each of said plurality of applications; calculating resource consumption ratio of each of said plurality of applications; and analyzing resource consumption of a plurality of currently co-existing applications.
Abstract:
A block-request streaming system provides for improvements in the user experience and bandwidth efficiency of such systems, typically using an ingestion system that generates data in a form to be served by a conventional file server (HTTP, FTP, or the like), wherein the ingestion system intakes content and prepares it as files or data elements to be served by the file server. A client device can be adapted to take advantage of the ingestion process as well as including improvements that make for a better presentation independent of the ingestion process. The files or data elements are organized as blocks that are transmitted and decoded as a unit, and the system is configured to provide and consume scalable blocks such that the quality of the presentation increases as more of the block is downloaded. Encoding and decoding blocks with multiple independent scalability layers can be done as well.