Abstract:
A method for adaptive content rendition includes receiving media content for playback to a user, adapting the media content for playback on a first device in the user's first location, receiving a notification when the user changes to a second location, adapting the media content for playback on a second device in the second location, and transitioning media content playback from the first device to the second device. The first device may be turned off after transitioning to the second device. The playback devices may be “dumb devices” which receive media content already prepared for playback, “smart devices” which receive media content in a less than ready form and prepare the media content for playback, or hybrid smart and dumb devices. A single device may be substituted by a plurality of devices. Adapting the media content may be based on a user profile storing user preferences and/or usage history.
Abstract:
A method and apparatus for a service platform capable of providing device-based task completion is disclosed. A request for a task is received at a service platform from a customer. A worker device to complete the task is selected from a group of worker devices registered with the service platform based on a current attribute of the worker device. Data resulting from completion of the task is received from the selected worker device, validated, and presented to the customer. A reward or incentive can be provided to the worker device in response to the data being received from the worker device and validated.
Abstract:
A method and apparatus for providing an opportunistic crowd based service platform is disclosed. A mobile sensor device is identified based on a current location and/or other qualities, such as intrinsic properties, previous sensor data, or demographic data of an associated user of the mobile sensor device. Data is collected from the mobile sensor device. The data collected from the mobile sensor device is aggregated with data collected from other sensor devices, and content generated based on the aggregated data is delivered to a user device.
Abstract:
A method and apparatus for providing an opportunistic crowd based service platform is disclosed. A mobile sensor device is identified based on a current location and/or other qualities, such as intrinsic properties, previous sensor data, or demographic data of an associated user of the mobile sensor device. Data is collected from the mobile sensor device. The data collected from the mobile sensor device is aggregated with data collected from other sensor devices, and content generated based on the aggregated data is delivered to a user device.
Abstract:
Speaker content generated in an audio conference is selectively visually represented. A profile for each audience member who participates in the audio conference is obtained. Speaker content spoken during the audio conference is monitored. Words of the speaker content are classified to have different weights according to a parameter of the profile for each of the audience members. A relation between the speaker content to the profile for each of the audience members is determined. Different visual representations of the speaker content are presented to different ones of the audience members based on the determined relation.
Abstract:
A content summary is generated by determining a relevance of each of a plurality of scenes, removing at least one of the plurality of scenes based on the determined relevance, and creating a scene summary based on the plurality of scenes. The scene summary is output to a graphical user interface, which may be a three-dimensional interface. The plurality of scenes is automatically detected in a source video and a scene summary is created with user input to modify the scene summary. A synthetic frame representation is formed by determining a sentiment of at least one frame object in a plurality of frame objects and creating a synthetic representation of the at least one frame object based at least in part on the determined sentiment. The relevance of the frame object may be determined and the synthetic representation is then created based on the determined relevance and the determined sentiment.
Abstract:
Disclosed herein are systems, methods, and computer-readable media for transmedia video bookmarks, the method comprising receiving a first place marker and a second place marker for a segment of video media, extracting metadata from the video media between the first and second place markers, normalizing the extracted metadata, storing the normalized metadata, first place marker, and second place marker as a video bookmark, and retrieving the media represented by the video bookmark upon request from a user. Systems can aggregate video bookmarks from multiple sources and refine the first place marker and second place marker based on the aggregated video bookmarks. Metadata can be extracted by analyzing text or audio annotations. Metadata can be normalized by generating a video thumbnail representing the video media between the first place marker and the second place marker. Multiple video bookmarks may be searchable by metadata or by the video thumbnail visually.
Abstract:
Disclosed herein are systems, methods, and computer-readable media for transmedia video bookmarks, the method comprising receiving a first place marker and a second place marker for a segment of video media, extracting metadata from the video media between the first and second place markers, normalizing the extracted metadata, storing the normalized metadata, first place marker, and second place marker as a video bookmark, and retrieving the media represented by the video bookmark upon request from a user. Systems can aggregate video bookmarks from multiple sources and refine the first place marker and second place marker based on the aggregated video bookmarks. Metadata can be extracted by analyzing text or audio annotations. Metadata can be normalized by generating a video thumbnail representing the video media between the first place marker and the second place marker. Multiple video bookmarks may be searchable by metadata or by the video thumbnail visually.
Abstract:
Disclosed herein are systems, computer-implemented methods, and tangible computer-readable media for representing media assets. The method includes receiving an original media asset and derivative versions of the original media asset and associated descriptors, determining a lineage to each derivative version that traces to the original media asset, generating a version history tree of the original media asset representing the lineage to each derivative version and associated descriptors from the original media asset, and presenting at least part of the version history tree to a user. In one aspect, the method further includes receiving a modification to one associated descriptor and updating associated descriptors for related derivative versions with the received modification. The original media asset and the derivative versions of the original media asset can share a common identifying mark. Descriptors can include legal documentation, licensing information, creation time, creation date, actors' names, director, producer, lens aperture, and position data.
Abstract:
Disclosed herein are systems, methods, and computer readable-media for rich media annotation, the method comprising receiving a first recorded media content, receiving at least one audio annotation about the first recorded media, extracting metadata from the at least one of audio annotation, and associating all or part of the metadata with the first recorded media content. Additional data elements may also be associated with the first recorded media content. Where the audio annotation is a telephone conversation, the recorded media content may be captured via the telephone. The recorded media content, audio annotations, and/or metadata may be stored in a central repository which may be modifiable. Speech characteristics such as prosody may be analyzed to extract additional metadata. In one aspect, a specially trained grammar identifies and recognizes metadata.