Abstract: While a user views a primary content item (for example, a movie on a television screen), secondary content items are selected and presented to the user, either on the same screen or on a screen of the user's companion device. To choose selections that are relevant to the user's current interests, the selection process considers information beyond the realm of primary and secondary content. Over time, the selection process learns to make more relevant selections by monitoring selection choices made by other systems.

Abstract: Disclosed is a method of associating, at a secondary device, secondary media content with primary media content being output at a primary device. The method includes receiving, at the secondary device, first information based upon the primary content being output at the primary device, wherein the first information includes at least one of an audio and a visual signal, determining at the secondary device second information corresponding to the first information, receiving at the secondary device one or more portions of secondary media content that have been made available by a third device, determining at the secondary device whether one or more of the portions of the secondary media content match one or more portions of the second information, and taking at least one further action upon determining that there is a match.

Abstract: In one embodiment, a method includes launching an application on a first device. The application allows the first device to trigger a service based on a program being played on a second device. The first device captures a visual code being displayed in association with the program being played on the second device. The visual code includes encoded information for program ID information associated with the program being played on the second device and timing information associated with the program being played on the second device. The method determines the program ID information and the timing information from the encoded information included in the visual code and then triggers the service for the application using the timing information and the program ID information.

Abstract: Systems and methods for determining the location of advertisements in multimedia assets are disclosed. A method includes obtaining an audio signature corresponding to a time period of a multimedia asset, identifying a match between the obtained audio signature and one or more stored audio signatures, comparing programming data of the multimedia assets of the obtained audio signature and the matching audio signatures, and determining whether the time period of the multimedia asset contains an advertisement based on the comparison of the programming data of the multimedia assets of the obtained audio signature and the one or more matching audio signatures. Another method includes identifying matches between a plurality of obtained audio signatures and a plurality of stored audio signatures, and determining whether consecutive time periods of the multimedia asset contain an advertisement based on a number of consecutive matching audio signatures of the plurality of stored audio signatures.

Abstract: Particular embodiments provide a system to determine ad segments in a video asset to enable subsequent ad replacement in video programs. The system is included in a multiple service operator (MSO) system that broadcasts video programs via a broadcast schedule. The MSO may not know the location of the ad segments in the video asset. To determine the ad segments, the MSO uses a classifier to classify video program segments and advertisements in the video asset. The classifier may be integrated with an nDVR system. By integrating with the nDVR system, particular embodiments may determine user behavior information, such as trick play commands, from the nDVR system. The classifier may use the user behavior information to detect ad segments in the video asset. In one embodiment, the classifier may fuse outputs from different detectors to detect and validate ad segments in the video program.

Abstract: Particular embodiments analyze logos found in a video program to determine video demarcations in the video program. For example, a video demarcation may be content that marks (“marker content”) a transition from a first video content type to a second video content type. Marker content may be used so the user knows that a transition is occurring. Particular embodiments analyze the logos found in a video program to determine the video demarcations in the video. The video is first analyzed to determine logos in the video program. Once these logos are determined, particular embodiments may re-analyze the video program to identify marker frames that include the marker content that signal the transitions to a different video content types. The marker frames may be determined without any prior knowledge of the marker content. Then, particular embodiments may use the marker frames to determine video segments.

Abstract: A method of identifying a representative image of a video stream is provided. Similarity between video frames of a primary video stream relative to video frames of a different secondary video stream having similar content is evaluated and a video frame from the primary video stream having a greatest extent of similarity relative to a video frame of the secondary video stream is identified. The identified video frame is selected as an image representative of the primary video stream and may be used as an informative thumbnail image for the primary video stream. A video processing electronic device and at least one non-transitory computer readable storage medium having computer program instructions stored thereon for performing the method are also provided.

Abstract: Particular embodiments automatically identify and track a logo that appears in video content. For example, particular embodiments can track a branding logo's position and size without any prior knowledge about the logo, such as the position, type, structure, and content of the logo. In one embodiment, a heat map is used that accumulates a frequency of short-term logos that are detected in the video content. The heat map is then used to identify a branding logo in the video content.

Abstract: Particular embodiments detect a solid color frame, such as a black frame, that may include visible content other than the solid color in a portion of the frame. These frames may conventionally not be detected as a solid color frame because of the visible content in the portion of the frame. However, these solid color frames may be “functional” black or white frames, in that the solid color frames are performing the function of the solid color frame even though the frames include the visible content. The visible content may be content that may always be displayed on the screen even if the video content is transitioning to an advertisement. Particular embodiments use techniques to detect the functional solid color frames even when visible content appears in the solid color frames. Particular embodiments use color layout information and edge distribution information to detect solid color frames.

Abstract: Particular embodiments provide supplemental content that may be related to video content that a user is watching. A segment of closed-caption text from closed-captions for the video content is determined. A first set of information from the segment of closed-caption text, such as terms may be extracted. Particular embodiments use an external source that can be determined from a set of external sources. To determine the supplemental content, particular embodiments may extract a second set of information from the external source. Because the external source may be more robust and include more text than the segment of closed-caption text, the second set of information may include terms that better represent the segment of closed-caption text. Particular embodiments thus use the second set of information to determine supplemental content for the video content, and can provide the supplemental content to a user watching the video content.

Abstract: Devices and methods for scoring viewer's interactions with content broadcast on a presentation device by processing at least one audio signal received by a microphone proximate the viewer and the presentation device, to generate at least one audio signature, which is compared to at least two different reference audio signatures.

Abstract: Devices and methods that match audio signatures to programming content stored in a remote database are disclosed. In one aspect of an embodiment, audio that includes primary audio from a device that outputs media content to one or more users is analyzed, in order to identify a presence or absence of corruption, and an audio signature is generated for an interval of time. In an aspect of a further embodiment, content being watched by a user is identified using a query audio signature and a message indicating the presence or absence of corruption.

Abstract: A method of identifying a representative image of a video stream is provided. Similarity between video frames of a primary video stream relative to video frames of a different secondary video stream having similar content is evaluated and a video frame from the primary video stream having a greatest extent of similarity relative to a video frame of the secondary video stream is identified. The identified video frame is selected as an image representative of the primary video stream and may be used as an informative thumbnail image for the primary video stream. A video processing electronic device and at least one non-transitory computer readable storage medium having computer program instructions stored thereon for performing the method are also provided.

Abstract: A method of detecting frames in a video that demarcate a pre-determined type of video segment within the video is provided. The method includes identifying visually distinctive candidate marker frames within the video, grouping the candidate marker frames into a plurality of groups based on visual similarity, computing a collective score for each of the groups based on temporal proximity of each of the candidate marker frames within the group to related events occurring within the video, and selecting at least one of the groups based on the collective proximity scores as marker frames that demarcate the pre-determined type of video segment. A video processing electronic device and at least one non-transitory computer readable storage medium having computer program instructions stored thereon for performing the method are also provided.

Abstract: A video processing device includes a histogram generating component, an analyzing component, a comparator and an encoding component. The histogram generating component can generate a histogram for image data of an image frame. The analyzing component can analyze the histogram, can identify an isolated spike in the histogram and can output at least one strobe parameter. The comparator can compare the at least one strobe parameter with at least one predetermined threshold, can output a first instruction signal when the at least one comparison operation is indicative of a strobe and can output a second instruction signal when the at least one comparison operation is not indicative of a strobe. The encoding component can encode the image data in a first manner based on the first instruction signal and can encode the image data in a second manner based on the second instruction signal.

Abstract: Systems, methods, and devices for an interactive viewing experience by detecting on-screen data are disclosed. One or more frames of video data are analyzed to detect regions in the visual video content that contain text. A character recognition operation can be performed on the regions to generate textual data. Based on the textual data and the regions, a graphical user interface (GUI) definition to can be generated. The GUI definition can be used to generate a corresponding GUI superimposed onto the visual video content to present users with controls and functionality with which to interact with the text or enhance the video content. Context metadata can be determined from external sources or by analyzing the continuity of audio and visual aspects of the video data. The context metadata can then be used to improve the character recognition or inform the generation of the GUI.

Abstract: A video processing system detects an overlay image, such as a logo, in a picture of a video stream, the overlay for example being a broadcaster's logo. The detection is based on evaluation of blending characteristics of a picture frame. The method of detection of an overlay defines first and second areas within the image, the first and second areas being non-overlapping. Next an alpha-blended value is calculated for the mean color value of the second area with an overlay color value. Then, if the mean color value of the first area is closer to the alpha-blended value than it is to the mean color value of the second area, the overlay can be indicated as detected and defined within the picture. Detection of the overlay can be used to identify an owner of the video, or detect when a scene change such as a commercial occurs.

Abstract: A method of classifying the shot type of a video frame, comprising loading a frame, dividing the frame into field pixels and non-field pixels based on a first playfield detection criteria, determining an initial shot type classification using the number of the field pixels and the number of the non-field pixels, partitioning the frame into one or more regions based on the initial classification, determining the status of each of the one or more regions based upon the number of the field pixels and the non-field pixels located within each the region, and determining a shot type classification for the frame based upon the status of each the region.

Abstract: A video processing system detects an overlay image, such as a logo, in a picture of a video stream, the overlay for example being a broadcaster's logo. The detection is based on evaluation of blending characteristics of a picture frame. The method of detection of an overlay defines first and second areas within the image, the first and second areas being non-overlapping. Next an alpha-blended value is calculated for the mean color value of the second area with an overlay color value. Then, if the mean color value of the first area is closer to the alpha-blended value than it is to the mean color value of the second area, the overlay can be indicated as detected and defined within the picture. Detection of the overlay can be used to identify an owner of the video, or detect when a scene change such as a commercial occurs.

Abstract: A method receives video content and metadata associated with video content. The method then extracts features of the video content based on the metadata. Portions of the visual, audio, and textual features are fused into composite features that include multiple features from the visual, audio, and textual features. A set of video segments of the video content is identified based on the composite features of the video content. Also, the segments may be identified based on a user query.