Abstract: The described technology is generally directed towards developing an adaptive bitrate stack (ladder) on a per-title basis. Variable bitrate encodings are used to obtain complexity information for a title and per-frames scores for the encodings; another encoding provides scene data. The complexity information is analyzed and processed based on the scene data to determine scene-based (e.g., objective and/or subjective quality) scores, which are used to determine scores for the encodings. The results are used to derive a candidate stack, comprising various resolutions and bitrates that provide desirable results. The candidate stack is evaluated by encoding the title using the candidate stack. These encodings are evaluated to select one resolution from any duplicate resolutions for a bitrate (e.g., based on relative quality), resulting in a pruned, final ladder that is associated with the title as the adaptive bitrate stack to be used for streaming that title's content.

Abstract: The described technology is directed towards having UI elements structured in a hierarchical configuration, in which parent and child UI elements communicate via a virtualization interface. A change to any parent UI element view propagates to each impacted descendant, e.g., each child, any children of that child and so on, whereby each child can manage virtualization and rendering based upon the change. Focus changes among the UI elements are also handled by propagating information via the virtualization interface.

Abstract: Determining the rendering of user interface (UI) elements, referred to as views, based upon styleable transitions between possible states of a view. Transitions may include animation, such as to smoothly enter a view into or exit a view out of a scene over a number of rendering frames. Transitions also may be applied to view state changes related to a UI element, such as to indicate hovered over, focused, listening (for speech), selected and/or pressed. View state changes also may be animated.

Abstract: The described technology is generally directed towards validating content selection graphs for use in an in-memory content selection graph data store. When a content selection graph data is generated, the graph nodes can correspond to prebuilt response data. The response data for any of the nodes can be verified against rules based on the type of a node, for example, as well as based on client-specific information for types of clients. The overall validation process can validate the content selection graph for subsequent use, can result in errors or warnings being logged (which may or may not render the graph unusable, e.g., depending on severity), or can fail the content selection graph. If validated, the content selection graph can be used to rapidly return response data when content from the graph is requested.

Abstract: The described technology is generally directed towards maintaining content selection graphs in an in-memory content selection graph data store in association with respective start times that indicates when the respective graphs become active. When a request to return content selection data is received, an active graph that corresponds to the request and the current time is accessed to obtain the requested content selection data. The response data can be prebuilt, e.g., in a set of active graphs for different client types, so that the response can be returned generally as is from the active graph in the set for that particular client type. A Redis cache can be used to maintain the various graph sets, including the active graph sets and graph sets that will become active at a future time.

Abstract: The described technology is generally directed towards coordinating the generation, validation and enabling of content selection graphs in an in-memory content selection graph data store. When a set of content selection graphs is requested, a coordinator starts the generation of the relevant graphs. Upon successful generation, the coordinator starts a validation of the generated graphs against rules for the nodes/response data in the graphs. If the generated graphs pass validation, the coordinator enables the graph set for use in an in-memory cache, whereby when a request to return content selection data is received, an active graph that corresponds to the request and the current time is accessed to obtain and return the response data as the requested content selection data.

Abstract: The described technology is generally directed towards predicting a need for provisioned (e.g., cloud computing) resources so that the provisioned resources are proactively provisioned and operational before their actual need. Historical data is used to predict upcoming resource demand so that resources begin to be scaled up to meet demand in advance, at a prediction time, given that there is a “spin-up” delay between requesting resources and their actual availability. The predictive resource provisioning is adaptable to override customary historical data with expected exceptions, and is flexible to handle variable spin-up times, constraints, and optimizations.

Abstract: The described technology is generally directed towards integrated tools for editing and otherwise working with close-captioning captions (or subtitles), including an on-screen editing interface that allows a user to select and edit caption text directly on-screen. Caption editing can include changing positioning metadata associated with a caption, changing timing metadata associated with a caption, and/or changing text content/text style metadata of a caption. A counter is provided to assist the user with respect to how many additional characters can be added to the caption. Also provided is a search interface that locates captions within a large set of captions, such as the full set of captions for a video.

Abstract: The described technology is directed towards an image providing service, including an image processing service that composites a base image into a resultant image, e.g., by resizing an image, overlaying text and so forth based upon a purpose for that image and/or a client device class; other parameters such as design information, protection and so forth also may be specified. When a client requests an image including by specifying a purpose and size in a request to an endpoint (e.g., URL) for an image, the image processing service locates or composites a resultant image corresponding to the request, and returns the resultant image or a modified (e.g., resized) resultant image in response to the request. Clients thus obtain images based upon a desired purpose without having to do client-side image processing including image compositing.

Abstract: The described technology is generally directed towards comparing two images for content differences, such as images based on the frames of a show and a derivative version of that show. Frame pairs such as from an original show and its derivative version are processed into image pairs, which can include decoding, scaling, luminance extraction and/or filtering. An edge pixel image is obtained via edge detection for each image. Edge pixels in one image are compared against a counterpart edge pixel (and possibly neighboring pixels) in the other image to determine matches (matching edge pixels) and mismatches. An image with too many errors based on the mismatches is deemed as a candidate for further review. A difference image can be generated to assist a reviewer in detecting where the mismatches were detected. By repeating for the various frames, a show can be automatically compared against its derivative for content differences.

Abstract: The described technology is directed towards returning less data than is available for a data item in response to a request to a data service. A virtual graph node is returned in response to client requests, in which the virtual node comprises a relatively lightweight set of information relative to the full set of information for the data item, e.g., maintained in a main (graph) node. A requesting client indicates that a virtual node is desired, and receives a response comprising the virtual node, generally processed from the main node's data into a reduced subset of the main node. The main node may be cached at the data service, and returned if and when requested.

Abstract: A technology that streams graphical components and rendering instructions to a client device, for the client device to perform the final rendering and overlaying of that content onto the client's video stream based on the client's most recent tracking of the device's position and orientation. A client device sends a request for augmented reality drawing data to a network device. In response, the network device generates augmented reality drawing data, which can be augmented reality change data based on the augmented reality information and previous client render state information, and sends the augmented reality drawing data to the client device. The client device receives the augmented reality drawing data and renders a visible representation of an augmented reality scene comprising overlaying augmented reality graphics over a current video scene obtained from a camera of the client device.

Abstract: The described technology is generally directed towards pull locomotion, which allows users to move around a virtual reality environment (typically larger than their physical environment) by interacting with pull targets, which comprise interactive objects displayed in the reality environment. When (e.g., via a controller) the user reaches grabs a pull target and pulls the controller back towards the user, the user's perceived position moves toward the target, as if the environment is being pulled to the user. A push motion generally results in moving the user's perceived position away from the target. The perceived movement can be gradual in the environment, relative to the speed of the pull or push. The pulling and pushing facilitate an interactive narrative experience or enhance interactive game play.

Abstract: The described technology is directed towards generating a new video image sequence (e.g., for playback at 30 frames per second) based on an existing video image sequence (e.g., originated for playback at 24 frames per second). The technology is based on processing frames, e.g., adjacent pairs of frames in a four-frame sequence, to obtain candidate frames for selecting a similar candidate frame to insert into the original sequence to create the new sequence (e.g., a five-frame sequence). Aspects include selecting a repeated frame to insert or creating a new frame from existing frames to insert, to generate the new sequence based on a difference/scoring comparison.

Abstract: The described technology is generally directed towards garbage collecting content selection graphs and related data from in an in-memory content selection graph data store. When a set of content selection graphs expire, a more current content selection graph set becomes active, and the storage space (e.g., in a Redis cache) used by the expired content selection graphs is reclaimed via garbage collection. Some graphs can be replaced before use, referred to as orphaned graphs, and the storage space for any such orphaned graphs is also reclaimed during garbage collection. Also garbage collected is storage space including related data structures used to generate and validate graphs.

Abstract: The described technology is directed towards a production shot design system that facilitates previsualizing scene shots, including by members of a production crew (running client devices) in different locations in a collaborative and secure shot construction environment. Modifiable scene elements' properties and camera data can be manipulated to build a scene (shot) containing modifiable and non-modifiable scene elements. In an online, shared camera mode, changes to a scene can be communicated to other client devices, e.g., virtually immediately, so that each client device displays the change for other users to see at an interactive frame rate. Scene changes can also be made locally and/or in an offline mode before communicating to other users. In various aspects, animation and a video plane camera/video plane (e.g., greenscreen) are integrated into the production shot design system.

Abstract: The technology described herein is generally directed towards relating inconsistent identifiers of the same entertainment data entity (such as a movie) to one another. A global identification service, given an entertainment data entity identifier, returns identifier information and related data according to other naming conventions. Canonicalization rules and standards provide a consistent identifier for variously named/identified entertainment entities. A canonicalized identifier (or another identifier) may be part of a URN-based naming convention that identifies the entertainment data entity, as well as the organization that owns the entity and an authority within the organization that is responsible for that entertainment data entity.

Abstract: The described technology is generally directed towards causing the generation of a content selection graph (or set of graphs) upon receipt of a notification that a new graph or replacement graph is needed with respect to a starting timepoint. For a new graph, a timepoint for that new graph indicates the need for the new graph at a given starting time. For a replacement graph, a notification (subscribed from a monitoring service) can indicate that an existing graph has changed; a replacement graph is generated with a graph identifier of the replacement graph, which then replaces the graph identifier of the existing graph in the mappings of valid graphs to start times. A Redis cache can be used to maintain the various graph sets, including the active graph sets and graph sets that will become active at a future time.

Abstract: The described technology is directed towards a data transformation pipeline architecture of a data service that processes generalized datasets into datasets (e.g., video data or graph nodes) customized for a particular client device. Described herein is maintaining a set of data transformation models at a data service, and upon receiving a client request for data, selecting a relevant subset of the transformation models and arranging the subset into a data transformation pipeline. In general, the pipeline of transformation models transforms the generalized data into the format and shape that each client device expects. The subset may be selected based upon device type, device class and/or software version information (and possibly state data) sent with each data request. The transformation models may be maintained in a hierarchical data store such as files in a file system to facilitate retrieval by searching the hierarchy for appropriate transformation models.

Abstract: The described technology is generally directed towards providing a visible waveform representation of an audio signal, by processing the audio signal with a polynomial (e.g., cubic) mapping function. Coefficients of the polynomial mapping function are predetermined based on constraints (e.g., slope information and desired range of the resultant curve), and whether the plotted audio waveform corresponds to sound field quantities or power quantities. Once the visible representation of the reshaped audio waveform is displayed, audio and/or video editing operations can be performed, e.g., by time-aligning other audio or video with the reshaped audio waveform, and/or modifying the reshaped audio waveform to change the underlying audio data.