Abstract:
A method for optimizing the performance of an algorithm for detecting predetermined content in a media information stream, and a program and apparatus that operate in accordance with the method. The algorithm is a function of a set of parameters. The method comprises the steps of performing the algorithm at least once to detect the predetermined content in the media information stream, while employing a respective set of parameters in the algorithm for each performance thereof, and automatically evolving at least one respective set of parameters employed in the algorithm to maximize the degree of accuracy at which the algorithm detects the predetermined content in the media information stream.
Abstract:
A method for selecting a chapter boundary for a digital video recording is provided that includes examining cut-rates for the recording. A determination is made regarding whether a default chapter length has passed. A determination is made regarding whether the cut-rate for the recording at the default chapter length is low. The chapter boundary is selected at the default chapter length when the cut-rate for the recording at the default chapter length is low.
Abstract:
Techniques are disclosed for detecting commercials or other particular types of video content in a video signal. In an illustrative embodiment, color histograms are extracted from frames of the video signal. For each of at least a subset of the extracted color histograms, the extracted color histogram is compared to a family histogram. If the extracted color histogram falls within a specified range of the family histogram, the family histogram is updated to include the extracted color histogram as a new member. If the extracted color histogram does not fall within the specified range of the family histogram, the family histogram is considered complete and the extracted color histogram is utilized to generate a new family histogram for use in processing subsequent extracted color histograms. The resulting family histograms are utilized to detect commercials or other particular type of video content in the video signal.
Abstract:
A video indexing system analyzes contents of source video and develops a visual table of contents using selected images. A system for detecting significant scenes detects video cuts from one scene to another, and static scenes based on DCT coefficients and macroblocks. A keyframe filtering process filters out less desired frames including, for example, unicolor frames, or those frames having a same object as a primary focus or one primary focuses. Commercials may also be detected and frames of commercials eliminated. The significant scenes and static scenes are detected based on a threshold which is set based on the category of the video.
Abstract:
The process of compressing video requires the calculation of a variety data that are used in the process of compression. The invention exploits some or all of these data for purposes of content detection. For example, these data may be leveraged for purposes of commercial detection. The luminance, motion vector field, residual values, quantizer, bit rate, etc. may all be used either directly or in combination, as signatures of content. A process for content detection may employ one or more features as indicators of the start and/or end of a sequence containing a particular type of content and other features as verifiers of the type of content bounded by these start/end indicators. The features may be combined and/or refined to produce higher-level feature data with good computational economy and content-classification utility.
Abstract:
Customizable multimedia content is transmitted in a form where some content is described by content descriptors. The content descriptors are used in the receiving device to synthesize a final version of the content. Content descriptors may include information relating to content length, expecting user mood, expected user location, content type, expected time of day of receipt, expected display device, and/or language in which the content is described. Local information may be used to inform the synthesis process. Local information may include user preferences generated from a user profile, context information detected automatically, or user preferences entered manually by a user. Alternatively, some synthesis instructions may be part of the content descriptors. Synthesizing creates a presentation of the content which may include a synthesized person, a cartoon character, an animal, a talking object, text, and/or audio.