Koninklijke Philips Corporation N.V.

Philips Electronics North America Corporation

North American Philips Corporation

Thomas F McGee

Nevenka Dimitrova

Lalitha Agnihotri

Vivek Mehrotra

Jan Hermanus Elenbaas

Susan McGee

Radu S Jasinschi

Hemant S Betrabet

Jan Herman Elenbaas

Jeroen Langevoort

Edward Young

Mauro Barbieri

J David Schaffer

Gerhardus Engbertus Mekenkamp

Serhan Dagtas

Edwin Salomons

Gabriel M Loiacono

Sylvie Jeannin

Nicholas Joseph Mankovich

Richard A Stolzenberger

Aaron S Mendelsohn

Gerard M Blom

George Kostecky

A method of selecting, storing and delivering desired audio/data/visual information includes the steps of determining viewing preferences of a viewer and receiving a first group of audio/data/visual signals, for example, broadcast and cable television signals or internet-based signals. Based on the first group of audio/data/visual signals, a second group of audio/data/visual signals, which is a subset of the first group of audio/data/visual signals, is identified. The second group of audio/data/visual signals is selected based on the association of EPG data for each signal with the viewing preferences of the viewer. Content data is then extracted from the second group of audio/data/visual signals and compared with the viewing preferences. The content data may include, for example, closed-captioned text, EPG data, audio information, visual information and transcript information. Based on the comparison of the content data extracted from the second group of audio/data/visual signals with the viewing preferences, audio/data/visual information contained in the second group of audio/data/visual signals which is of interest to the viewer is identified and stored for review at the viewers convenience.

Method and apparatus for audio/data/visual information

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.

Method, apparatus, and program for evolving algorithms for detecting content in information streams

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.

Method and system for selecting chapter boundaries for digital video recordings

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.

Family histogram based techniques for detection of commercials and other video content

A method, apparatus and systems for bookmarking an area of interest of stored video content is provided. As a viewer is watching a video and finds an area of interest, they can bookmark the particular segment of the video and then return to that segment with relative simplicity. This can be accomplished by pressing a button, clicking with a mouse or otherwise sending a signal to a device for marking a particular location of the video that is of interest. Frame identifiers can also be used to select a desired video from an index and to then retrieve the video from a medium containing multiple videos.

Streaming video bookmarks

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.

Significant scene detection and frame filtering for a visual indexing system using dynamic thresholds

Advertisers want to deliver their message in a relatively short period of time. This leads to the product name, company name and other identifying features being repeated frequently during a commercial broadcast. Transcript information can be used to detect commercials by detecting frequently occurring words in the commercials. This can also be used to identify an individual commercial from other commercials. Once the individual commercials have been identified, the transcript information corresponding to each commercial can be stored in a database to identify the commercial in subsequent broadcasts, or to provide a search mechanism for searching a particular commercial in the database.

Method of using transcript information to identify and learn commercial portions of a program

A video signal is processed to generate one or more signatures associated with a broadcast program to be recorded by a recording device. The signatures are then processed to determine an actual start time and end time of the desired broadcast program, such that the program can be properly recorded despite delays or other changes in a pre-scheduled broadcast time of the program. One or more of the extracted signatures may be based at least in part on, e.g., a keyframe similarity measure, a histogram, one or more detected commercials, a transcript, a program logo or other detected object, detected text, and a sign-on or sign-off of the desired program. Other types of signatures can also be used.

Methods and apparatus for recording programs prior to or beyond a preset recording time period

A video indexing method and device for selecting keyframes from each detected scene in the video. The method and device detects fast motion scenes by counting the number of consecutive scene changes detected.

Method and apparatus for detecting fast motion scenes

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.

Video content detection method and system leveraging data-compression constructs

A video signal is processed to identify segments that are likely to be associated with a commercial or other particular type of video content. A signature is extracted from each of the segments so identified, and the extracted signatures are used, possibly in conjunction with additional temporal and contextual information, to determine which of the identified segments are in fact associated with the particular video content. One or more of the extracted signatures may be, e.g., a visual frame signature based at least in part on a visual characteristic of a frame of the video segment, as determined using information based on DC and motion coefficients of the frame, or DC and AC coefficients of the frame. A given extracted signature may alternatively be an audio signature based at least in part on a characteristic of an audio signal associated with a portion of the video segment. Other types of signatures can also be used. Advantageously, the invention allows the identification and extraction of particular video content to be implemented with significantly reduced amounts of memory and computational resources.

Automatic signature-based spotting, learning and extracting of commercials and other video content

A video indexing system analyzes contents of source video and develops a visual table of contents using selected images. The source video is analyzed to detect video cuts from one scene to another, and static scenes. Keyframes are selected for each significant scene. 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. A visual index is created from those frames remaining after the keyframe filtering and stored for retrieval. The visual index may be retrieved by a user who may then display the visual index on a display. The user may select one of the frames displayed in the visual index and the source video may be manually (by the user) or automatically advanced to that frame of the source video. Additionally, a user may print the visual index.

Visual indexing system

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.

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Peekskill, NY, United States of America

Thomas F McGee